Neurology

Physiological predictors of respiratory motor plasticity: A machine-learning reappraisal of phrenic motor facilitation.

Acute intermittent hypoxia (AIH)-induced phrenic long-term facilitation (pLTF) is a well-established...

MRI-based machine learning model to distinguish hippocampal sclerosis (HS) ILAE type 1 and no HS gliosis only in medial temporal lobe epilepsy.

PURPOSE: Despite recent advances in preoperative work-up of drug resistant medial temporal lobe epil...

Machine learning and meningitis prediction in pediatric invasive pneumococcal disease: a retrospective single-center study.

Evaluating data heterogeneity's impact on convolutional neural network performance in medical imaging.

PURPOSE: Machine learning in medical imaging (MIML) is critical to computer-aided diagnostics. Howev...

Enhancing Target Recognition Performance in SSVEP-Based Brain-Computer Interfaces via Deep Neural Networks with Pyramid Squeeze Attention.

Steady state visual evoked potential (SSVEP)-based brain-computer interfaces have been widely studie...

Exploring Information Access in Aging Populations and Those With Dementia and Mild Cognitive Impairment in the United Kingdom: Survey and Focus Group Study.

BACKGROUND: With the growing aging population, technology that supports independent living is increa...

Establishment and validation of an Alzheimer's disease diagnostic model on the basis of exhaled volatile organic compound characteristics.

Exhaled volatile organic compounds (VOCs) have been investigated in some diseases, including cogniti...

A framework for the exploration of subcellular compartmentalization of RNA-binding proteins.

The ability of RNA-binding proteins to form complexes with other biomolecules underpins a broad rang...

Identification and Experimental Validation of Biomarkers Associated with PI3K/AKT Signaling Pathway in Spinal Cord Injury.

Spinal cord injury (SCI) refers to trauma to the spinal cord resulting in functional deficits. Dysre...

The utility of Speech and Language analytics for screening Alzheimer's Disease.

BACKGROUND: Effective screening and cohort enrichment remain major challenges in clinical trials for...

An AI Based Screening Tool for Detection of Cerebral Venous Thrombosis on Non-Contrast Brain CT.

While non-contrast computed tomography (NCCT) is the primary ‎imaging modality in emergency settings...

SSiamese Capsule Network (SNNCap) : Cognitive Analysis for Alzheimer's Disease Classification from MRI Data.

Alzheimer's Disease (AD) detection is essential for timely treatment and better patient care. Magnet...

Neuromodulation-induced normalization of cortical metastable dynamics signatures in Parkinson's disease.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) alleviates motor symptoms in Parkinson...

Cerebral Vasospasm Detection and Delayed Cerebral Ischemia Prediction after Aneurysmal Subarachnoid Hemorrhage: A Scoping Review.

BACKGROUND/OBJECTIVE: Aneurysmal subarachnoid hemorrhage (aSAH) is complicated by angiographic cereb...

AI-Driven Multi-parametric MS Lesion Analysis from T2-FLAIR Imaging: a Clinical Decision Support Framework for Neuroradiology.

Artificial intelligence (AI) is transforming neuroradiological practice, yet multiple sclerosis (MS)...

Evolving role of biomarkers in spinal cord injury: From research to clinical translation.

Spinal cord injury (SCI) triggers a complex cascade of cellular and molecular events at the lesion s...

The use of artificial intelligence in headache medical and patient education: Generation of visual aids.

Deciphering the molecular network of Trichostatin A in regulating Alzheimer's disease screening of core genes and mechanistic investigation based on multidimensional bioinformatics and molecular simulation.

BACKGROUND: Histone deacetylases (HDACs) regulate neuroprotection; however, Trichostatin A (TSA), an...

CDR-Net: A computerized framework to detect Alzheimer's diseases and mild cognitive impairment.

Alzheimer's disease (AD) and mild cognitive impairment (MCI) are two dementia-related brain illnesse...

Predicting future cognitive impairment in preclinical Alzheimer's disease using amyloid PET and MRI: A multisite machine learning study.

Predicting the likelihood of developing Alzheimer's disease (AD) dementia in at-risk individuals is ...

GRaph-based analysis for stroke prediction (GRASP): A multi-modal model for identifying first ischemic stroke in high-risk population using UK biobank.

BACKGROUND: Ischemic stroke accounts for 3.71 million deaths annually worldwide. Yet current risk pr...