Neurology

AI-driven low-cost rehabilitation exergame as a lightweight framework for stroke assessment.

Stroke is a leading cause of long-term disability, often affecting upper-limb motor function and req...

The role of brain health and resilience in reshaping trajectories of late-life neuropsychiatric disorders.

Global population aging and increased chronic stress due to numerous mass disasters including those ...

Mechanisms and biomarkers of poststroke cognitive impairment.

Poststroke cognitive impairment is a common neurological complication in stroke patients, characteri...

Multi-omics prediction of key proteases regulating scar formation and neural repair after spinal cord injury.

Neurological injury is often accompanied by extensive infiltration of macrophages along with activat...

Correlation between oral disease and neurodegenerative disorders: Role of biological proteins for the modulation of oral-brain axis and gut-brain axis.

Biological proteins play a crucial role at the intersection of oral health and neuroscience, offerin...

Comparing the cognitive-motor performance of individuals with temporal lobe epilepsy versus healthy controls using robotics.

Cognitive impairments are common in individuals with temporal lobe epilepsy (TLE). Interactive Kinar...

Dementia severity index: A threshold-based approach to classifying dementia levels using resting state EEG.

BACKGROUND: Alzheimer's Disease (AD) and FrontoTemporal Dementia (FTD) are dementia conditions that ...

AI-Enabled Sensing Wristband for Student Behavior Detection.

With the advancement of the Internet of Things (IoT) and artificial intelligence (AI) technologies, ...

[Current status and future perspectives of endoscopic surgery for cervical radiculopathy].

Cervical radiculopathy is one of the common degenerative disorders encountered in spinal surgery. Wi...

An integrative clinical and bioinformatic analysis identifies MicroRNAs as biomarkers of ischemic stroke severity.

Identifying reliable circulating biomarkers is crucial for improving the diagnosis and risk stratifi...

Converse or reverse? Machine-learning modeling for disease progression: A study based on Alzheimer's disease continuum cohort.

INTRODUCTION: Longitudinal trajectories from healthy aging to Mild Cognitive Impairment and Alzheime...

Prediction of medication overuse in patients with migraine using cox regression and machine learning: a real-world cohort.

Organic Transistor-Based Neuromorphic Electronics and Their Recent Applications.

Neuromorphic technologies offer a promising pathway to address the escalating energy demands of arti...

Peptide-nanoparticle platforms for antisense therapeutics: A coarse-grained modeling approach to brain delivery.

Traumatic brain injury (TBI) is a leading cause of long-term neurological deficits, often resulting ...

Generating synthetic MRI scans for improving Alzheimer's disease diagnosis.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the leading cause of dement...

LMSA-net: a lightweight multi-scale attention network for eeg-based emotion recognition.

Electroencephalogram (EEG)-based emotion recognition holds great potential in affective computing, m...

[Wolff-Parkinson-White syndrome : Comparison of different algorithms].

BACKGROUND: Wolff-Parkinson-White (WPW) syndrome is characterised by accessory pathways that bypass ...

On-device single channel EEG classification on Android smartphones using lightweight machine learning models.

OBJECTIVE: Electroencephalogram (EEG) signals capture neuronal activity by measuring electrical acti...

Influence of personalized human head modeling and resolution on EEG source localization for rapid brain mapping.

OBJECTIVE: To evaluate the trade-offs among model resolution, anatomical fidelity, computational cos...

Evaluation of the neurotrophic peptide mixture in pathogenetic therapy of patients with Parkinson's disease.

This exploratory, single-group, open-label study investigated 17 patients with Parkinson's disease (...

Recognizing the feature of knee hyperextension in stroke patients based on transformer-long-short-term memory model.

BACKGROUND: Recognizing knee hyperextension during gait in stroke patients is clinically challenging...