Neurology

Generative large language models in the clinical management of Alzheimer's disease and mild cognitive impairment.

BACKGROUND: Dementia affects over 55 million people worldwide. Mild cognitive impairment (MCI) often precedes Alzheimer's disease (AD). Clinical management requires integrating uncertain evidence from neuropsychological testing, neuroimaging, and biomarkers. Large language models (LLMs) also generate probabilistic outputs, but whether they can reliably support diagnostic, therapeutic, or education...

Wearable fatigue detection system for wheelchair propulsion: Identifying key muscles via an attention-based LSTM Model.

Fatigue induces adverse short- and long-term health risks in wheelchair users. This study aimed to develop a machine learning approach to predict fatigue onset during wheelchair incremental exercise via surface electromyography (sEMG). sEMG from eight upper-limb muscles and oxygen uptake data were collected from nine wheelchair users (3 females, 6 males) performing incremental wheelchair propulsio...

Deep-learning based electroencephalogram denoising: A literature review.

Electroencephalography (EEG) is a pivotal tool for exploring brain functions. However, the low amplitude of EEG signals renders them inherently suscep...

Multimodal quantification of cognitive load using a printed wearable facial bio-potential system.

Cognitive load refers to the amount of mental effort required to process information and perform tasks. It has a strong impact on both learning and ta...

Surface circumferential spinal cord recording in freely moving rodents.

Spinal cord injury affects over 2.5 million people worldwide, yet current neuroprosthetic strategies remain fragmented, addressing motor, sensory, or ...

Comparative effectiveness of arthroscopic-assisted uniportal surgery versus percutaneous endoscopic decompression in lumbar spinal stenosis.

Single-level lumbar spinal stenosis (LSS) that does not respond to conservative therapy is now of the standard care given due to minimal invasive deco...

Portable RF brain scanner enables stroke type detection using deep learning.

Stroke remains a leading cause of mortality worldwide, demanding rapid, accurate diagnosis; distinguishing stroke types matters because treatments dif...

Feasibility of using artificial intelligence models to identify the obturator nerve in laparoscopic selective lateral pelvic lymph node dissection.

BACKGROUND: Protecting the obturator nerve (ON) is crucial during selective lateral pelvic lymph node dissection (SLPLND). This study evaluated the fe...

Machine learning-enabled behavioural and psychological symptoms of dementia management intervention for dementia caregivers: protocol for a hybrid factorial SMART-MRT trial.

BACKGROUND: Behavioural and psychological symptoms of dementia (BPSD) affect over 90% of people living with dementia and are a major contributor to st...

Optimizing the mathematical model and technical standards for unilateral biportal endoscopic spinal surgery through machine learning-based video analysis.

OBJECTIVE: To enhance the efficacy of the unilateral biportal endoscopic spinal procedure, the spinal triangle concept is proposed, integrating a digi...

Response to Letter to the Editor: Impact of 1024-Matrix Size on Perforating Artery Visualization in Cerebral CTA Using a 64-Slice CT Scanner.

This response addresses a Letter to the Editor commenting on our article on 1024-matrix reconstruction for perforating artery visualisation in cerebra...

Evaluating the impact of frailty in older adults on functional outcomes post-mechanical thrombectomy: a multicentre study incorporating traditional and machine learning methods.

Frailty is associated with high risk of mortality. Our study evaluated frailty as a predictor of outcomes in older adults with acute ischemic stroke t...

Frequency-decomposed EEG microstate analysis reveals altered cross-frequency coordination in adolescent major depressive disorder.

Adolescent major depressive disorder (MDD) involves alterations in large‑scale brain network dynamics. However, conventional EEG microstate studies ty...

Multilayer Validation Reveals a Glia-Associated Secretome Signature in Temporal Lobe Epilepsy.

Although multi-omics studies have increasingly revealed molecular alterations associated with epilepsy, clinically accessible cerebrospinal fluid (CSF...

A coarse-to-fine machine-learning framework for identifying functional connectivity markers of cognitive impairment in Parkinson's disease.

BACKGROUND: Resting-state functional MRI (rs-fMRI) has been applied to investigate cognitive impairment (CI) in Parkinson's disease (PD). Nevertheless...

Precision therapeutics and innovative clinical trial design in neurodegenerative diseases.

Neurodegenerative diseases are biologically heterogeneous disorders characterized by progressive neuronal dysfunction, overlapping molecular pathologi...

Unraveling Bone-Skin Crosstalk Enables miRNA Nanoformulation for Cutaneous Neurovascular Reconstruction in Diabetic Mice.

The clinical intractability of diabetic foot ulcers stems from a profound uncoupling of cutaneous neurovascular networks, rendering standard metabolic...

Cyclin-dependent kinases as signaling integrators in cancer: Structural evolution, functional plasticity, and drug discovery.

Cyclin-dependent kinases (CDKs), traditionally recognized for their pivotal role in cell cycle control, have emerged as versatile regulators orchestra...

Assessing the accuracy of ChatGPT responses to caregiver questions in pediatric neurology: an observational study.

ChatGPT has seen increased use by caregivers as a source of medical information. Pediatric neurology has added complexities because there are various ...

Semi-supervised ensemble learning with interval type-2 fuzzy-rough sets for Parkinson's disease prediction from multi-omics.

Parkinson's disease (PD) is a disorder involving progressive degeneration of the nervous system. Its clinical signs typically become noticeable only a...