Neurology

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 cognitive impairment, in pilot studies. The present study aimed to explore the role of exhaled VOCs in identifying and differentiating patients with Alzheimer's disease (AD). The identification cohort included 241 participants: 99 AD patients (dementia=74, mild cognitive impairment (MCI) = 25), 59 non-AD d...

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 range of structural properties and functions. Understanding the subcellular distribution of RNA-binding proteins and their interacting partners in the steady state and upon perturbation can therefore shed light on these aspects. Here, we present the compartmentalized RNA-Binding Protein (or coRBP) map, ...

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. Dysregulation of the phosphoinositide 3-kinase/serine-t...

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 Alzheimer's disease (AD), where traditional diagn...

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, it has a low sensitivity for detection of ‎Cereb...

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. Magnetic Resonance Imaging (MRI) is a technique in which...

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's disease (PD), but how it modulates whole-brain ...

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 cerebral vasospasm and delayed cerebral ischemia (DCI),...

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) diagnosis remains challenged by qualitative MRI a...

Prediction of Sustentaculum Tali Sustentacular Screw Length based on Linear Regression Model.

Calcaneal fractures present challenges due to the complex anatomy and difficulty in achieving precise screw placement. Traditional methods often rely ...

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 site, driving progressive degeneration of the spina...

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 HDAC inhibitor, lacks clear molecular mechanisms ...

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 illnesses that are prevalent among elders in the twenty-fi...

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 important for the design of and optimal recruitmen...

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 prediction models demonstrate modest discrimination ...

Adaptive dual-modality neuromodulation for chronic pain and muscle dysfunction: real-world insights from the NXTSTIM™ EcoAI digital platform.

BACKGROUND: Chronic musculoskeletal pain is often inadequately managed with pharmacologic therapy. Although transcutaneous electrical nerve stimulatio...

TransUNet for automated segmentation of intracranial aneurysms in digital subtraction angiography: A dual-center validation study.

PURPOSE: This study systematically evaluated five deep learning models to validate their consistency in deriving clinical morphological and quantitati...

Advancing brain age estimation: normative deviation mapping (NDM) for sensitive detection of pathological aging.

Brain age is a valuable neuroimaging-based biomarker for assessing brain health, typically estimated using machine learning (ML) models. However, ML a...

Visual function and cerebrospinal fluid volume along the optic nerve in patients with spontaneous cerebrospinal fluid rhinorrhea: a cross-sectional study.