Neurology

FKSUDDAPre: A drug-disease association prediction framework based on F-TEST feature selection and AMDKSU resampling with interpretability analysis.

In drug discovery and therapeutic research, the prediction of drug-disease associations (DDAs) holds significant scientific and clinical value. Drug molecules exert their effects by precisely identifying disease-related biological targets, systematically modulating the entire pharmacological process from absorption, distribution, and metabolism to final efficacy. Accurate prediction of drug-diseas...

TrkA abundance is increased in cutaneous nerves in bortezomib-induced neuropathy.

Tropomyosin receptor kinase A (TrkA), a high-affinity receptor for nerve growth factor (NGF), is implicated in nociception and local angiogenesis. We investigated TrkA localization and abundance in skin biopsies from multiple myeloma patients who developed peripheral neuropathy during bortezomib treatment. We recruited 50 multiple myeloma patients with bortezomib-induced peripheral neuropathy (BIP...

Integrating Regenerative Therapies and Artificial Intelligence for Precision Management of Diabetic Foot Ulcers.

SIGNIFICANCE: Diabetic foot ulcers (DFUs) represent one of the most devastating complications of diabetes, leading to high rates of amputation and mor...

Diagnosis of disorders of consciousness using nonlinear feature derived EEG topographic maps via deep learning.

This study explored the value of nonlinear features extracted from EEG signals to facilitate the assessment of patients with disorders of consciousnes...

Detecting isolated REM sleep behavior disorder at home using a lower-back wearable sensor.

Isolated REM Sleep Behavior Disorder (iRBD) is a strong predictor of neurodegenerative diseases, particularly synucleinopathies. Current diagnosis req...

Enhancing fMRI Decoded Neurofeedback with Co-adaptive Training: Simulation and Proof-of-principle Evidence.

A significant challenge for neurofeedback training research and related clinical applications, is participants' difficulty in learning to induce speci...

Dissociable impacts of perceived race and ascribed status in event-related brain potentials and multivariate network activity.

Humans rapidly and efficiently categorize others with limited information, forming split-second impressions. Prior EEG person perception research has ...

Comparative analysis of supervised and ensemble models with unsupervised exploration for alzheimer's disease prediction.

Alzheimer's disease is a progressive neurodegenerative disorder characterized by memory loss and cognitive decline, with no known cure. Early detectio...

Epileptic Seizure Detection from EEG Signals with Long Short-Term Memory-Transformer and Self-Supervised Learning.

Electroencephalogram (EEG) plays a vital role in seizure detection, yet existing methods often fail to adequately capture the spatiotemporal character...

A scoping review of portable ultra-low-field MRI studies in patients with acquired brain injury: Past, present, and future.

Acquired Brain Injury (ABI) refers to any post-birth damage to the brain, commonly resulting from traumatic events (traumatic brain injury) or non-tra...

Multiscale spatiotemporal neural network with multi-attention mechanism using brain partitioning for motor imagery recognition.

BACKGROUND: Motor imagery (MI)-based electroencephalogram (EEG) brain-computer interfaces (BCIs) facilitate communication for motor-impaired patients ...

Comprehensive segmentation of focal cortical dysplasia by combining surface-based and whole-brain MRI deep learning algorithms: a proof-of-concept study.

Introduction.Focal cortical dysplasia type II (FCD II) is a significant cause of drug-resistant epilepsy, and the full surgical resection of the lesio...

Effects of Robot-Assisted Gait Therapy on Urodynamic Changes in the Subacute Phase After Spinal Cord Injury: A Prospective Study.

BACKGROUND Approximately 70% to 84% of patients with spinal cord injury (SCI) have varying degrees of bladder dysfunction, which can lead to upper uri...

Spinal cord injury impact on skin temperature regulation during graded exercise: metaheuristic data mining-based predictions.

People with spinal cord injury (SCI) show impaired thermoregulation during exercise, making skin temperature a noninvasive indicator. This study appli...

Artificial intelligence-powered nanomedicine.

The escalating global burden of diseases-including cancer, neurodegenerative, and cardiovascular disorders-poses severe threats to human health and so...

Video-based diagnostics supported by artificial intelligence as an opportunity to address the epilepsy diagnostic gap: A narrative review.

Despite advancements in epilepsy care, a substantial diagnostic gap persists, particularly in resource-limited settings. This narrative review explore...

Protocol for Personalised Prediction of Persistent Postsurgical Pain.

INTRODUCTION: Persistent postsurgical pain (PPSP) affects up to 15% of patients after major surgery, impairing physical function, quality of life and ...

Validation of socialbit as a smartwatch algorithm for social interaction detection in a clinical population.

Social interaction supports brain health and recovery after neurological injury. Yet no validated tool exists for real-time measurement in individuals...

Utilizing optical coherence tomography and machine learning to identify vision abnormalities in pediatric neurofibromatosis type 1 patients.

Neurofibromatosis type 1 (NF-1) is a genetic disorder associated with a high risk of vision loss in children. Optical coherence tomography (OCT) provi...

An ensemble machine learning classifier for Parkinson's disease diagnosis using optical coherence tomography angiography.

Parkinson's disease (PD) is the fastest-growing neurodegenerative disorder worldwide, yet its early diagnosis remains a major challenge due to the abs...