Neurology

The presymptomatic and early manifestations of semantic dementia.

People with semantic dementia (SD) or semantic variant primary progressive aphasia typically present with marked atrophy of the anterior temporal lobe, and thereafter progress more slowly than other forms of frontotemporal dementia. This suggests a prolonged prodromal phase with accumulation of neuropathology and minimal symptoms, about which little is known. To study early and presymptomatic SD, ...

An epidemiological study of Parkinson's disease in Chinese older adults using the Global Burden of Disease and China Health and Retirement Longitudinal Study databases.

INTRODUCTION: The prevalence of Parkinson's disease (PD) has increased globally, especially in China, and emerged as a critical public health challenge. AIM OF THE STUDY: Based on the Global Burden of Disease (GBD) and the China Health and Retirement Longitudinal Study (CHARLS) databases, this study explores temporal trends in Parkinson's disease (PD) prevalence and its risk factors among middle-a...

Single-molecule detection of amino acid phosphorylation using electron tunnelling currents: toward neurodegenerative disease diagnosis.

Protein phosphorylation is one of the most prevalent post-translational modifications regulating biological functions, and its dysregulation is closel...

Machine learning approaches in predicting circadian rhythm sleep-wake disorders: A review.

Circadian rhythm sleep-wake disorders (CRSWDs) arise from misalignment between an individual's sleep-wake timing and endogenous circadian physiology, ...

Metabolic neural networks of the marmoset brain in awake and isoflurane-anesthetized resting states.

The common marmoset is a key model in translational neuroscience, yet the reliance on anesthesia for neuroimaging introduces significant confounds. To...

Protocol for cerebrospinal fluid analysis using enrichment-enhanced surface-enhanced Raman spectroscopy and transformer-enabled spectral classification.

The rapid detection and precise classification of cerebrospinal fluid in acute leukemia patients constitute a crucial clinical imperative. Here, we pr...

Data-driven detection of lucid episodes in advanced dementia: Application of latent class analysis to observational data.

BackgroundLucid episodes (LEs) in advanced dementia are significant clinical events yet are challenging to investigate as they are characterized by a ...

Expert Evaluation of the Perceived Accuracy, Relevance, and Safety of Large Language Model-Generated Patient Information in Geriatrics: Cross-Condition Study.

BACKGROUND: Large language models (LLMs) are increasingly used to generate patient-oriented medical information. In geriatrics, such information must ...

A novel feedback-based compensation reduction with upper body reconstruction for upper-limb rehabilitation.

Compensatory movements frequently occur during upper-limb rehabilitation for patients with stroke, potentially impeding effective motor recovery. Visi...

AI in Clinical Decision Support Systems: Promising Applications and Strategies for Managing Data Challenges.

The translation of big data analytics and artificial intelligence (AI) into clinical decision support systems (CDSSs) has advanced from proof of conce...

Deep Learning Radiomics Signature from Multicontrast MRI for Automated Identification of Symptomatic Carotid Plaques: A Multicenter Study.

BACKGROUND AND PURPOSE: Ischemic stroke poses a significant global health burden. Accurately identifying symptomatic carotid atherosclerotic plaques, ...

Learning patient-specific spatial biomarker dynamics via operator learning for Alzheimer's disease progression.

Alzheimer's disease (AD) is a complex, multifactorial neurodegenerative disorder with substantial heterogeneity in progression and treatment response....

Classification of spinal tuberculous infection, pyogenic infection and spinal metastasis from magnetic resonance imaging using machine learning.

BACKGROUND: Differentiating between spinal tuberculosis, pyogenic (bacterial) spondylitis and spinal metastasis remains a major diagnostic challenge b...

Screening macrophage polarization genes in spinal cord injury as therapeutic targets.

Macrophage polarization correlates strongly with the progression and prognosis of spinal cord injury (SCI), yet the therapeutic potential of macrophag...

Decoding the neural mechanisms of salty peptide perception via electroencephalography and machine learning.

Excessive sodium intake poses major public health risks, driving the search for salt substitutes that preserve desirable flavor. Salty peptides have e...

Reliability and readability of five AI chatbots for concussion health advice across retrieval augmented and pretrained models.

Generative AI is rapidly entering patient education workflows, yet its safety profile for concussion management remains undefined. Utilizing the CHART...

Identification of EEG features during status epilepticus for prediction of emergent epilepsy phenotype in the mouse intra-amygdala kainic acid model using supervised learning.

Preclinical animal models are essential for investigating epilepsy mechanisms and evaluating novel therapies. In rodents, epilepsy can be induced by s...

AI-Powered Gradient Echo Plural Contrast Imaging (AI-GEPCI)-A Comprehensive Neurological Protocol From a Single MRI Scan.

BACKGROUND: MRI is essential for diagnosing and monitoring neurological diseases. Conventional protocols require multiple sequences to obtain compleme...

Federated learning-enabled privacy-preserving framework for seizure forecasting and affective state analysis using multi-modal EEG-ECG data.

Seizure forecasting and affective state analysis using EEG-ECG data play a pivotal role in advancing neurological and mental health monitoring. Howeve...

Adaptive regression model for Parkinson's disease diagnosis from speech signals using Box-Cox-based clustering and extremely randomization.

Parkinson's Disease (PD) is a progressive neurodegenerative disorder that causes motor and cognitive impairments, affecting approximately 1% of indivi...