Neurology

Comparison of the effects of robot-assisted gait training using FES versus virtual reality for stroke patients. A randomized clinical trial.

BACKGROUND: Robot-assisted gait training is becoming an effective alternative to therapist-assisted gait training in stroke rehabilitation. This method has the potential to reduce therapist burden and treatment costs, and is receiving considerable attention for the functional recovery of stroke patients. OBJECTIVES: The purpose of this study was to compare the effects of robot-assisted gait traini...

The association between cerebral small vessel disease and unfavorable hematoma morphology in primary intracerebral hemorrhage.

OBJECTIVE: To study the association between cerebral small vessel diseases (CSVD) and unfavorable hematoma morphology in primary intracerebral hemorrhage (ICH).

Impact of three-dimensional prostate models during robot-assisted radical prostatectomy on surgical margins and functional outcomes.

BACKGROUND: Robot-assisted radical prostatectomy (RARP) is the standard surgical procedure for the treatment of prostate cancer. RARP requires a trade...

The role of neuro-imaging in multiple system atrophy.

Neuroimaging plays a crucial role in diagnosing multiple system atrophy and monitoring progressive neurodegeneration in this fatal disease. Advanced M...

Characterizing aging-related genetic and physiological determinants of spinal curvature.

BACKGROUND: Increased spinal curvature is one of the most recognizable aging traits in the human population. However, despite high prevalence, the eti...

Characteristics and Validity of Commercially Available Technologies Analyzing Voice Features to Assess Parkinson's Disease.

BACKGROUND: Interest in technologies for quantitative assessment of Parkinson's disease (PD) is growing, particularly those enabling voice and speech ...

Evaluating the Accuracy and Readability of ChatGPT in Addressing Patient Queries on Adult Spinal Deformity Surgery.

Study DesignCross-Sectional.ObjectivesAdult spinal deformity (ASD) affects 68% of the elderly, with surgical intervention carrying complication rates ...

Neural correlates of evaluative bias against AI-labeled versus human-labeled artworks.

The rapid advancement of generative artificial intelligence (AI) has enabled machines to produce creative outputs, such as artworks, that rival human ...

Short-horizon neonatal seizure prediction using EEG-based deep learning.

Strategies to predict neonatal seizure risk have typically focused on long-term static predictions with prediction horizons spanning days during the a...

Prediction of Cerebrospinal Fluid (CSF) Pressure with Generative Adversarial Network Synthetic Plasma-CSF Biomarker Pairing.

Non-invasive intracranial pressure (ICP) monitoring can help clinicians safely and efficiently monitor spaceflight-associated neuro-ocular syndrome (S...

An Efficient FoG-M3 Method for Self-Adaptive Labeling and Predicting Freezing of Gait.

Freezing of gait (FoG) is a common motor impairment that occurs as Parkinson's disease patients enter the moderate stage or higher, leading to a high ...

Acute Management of Nasal Bone Fractures: A Systematic Review and Practice Management Guideline.

Nasal bone fractures represent the most common facial skeletal injury, challenging both function and aesthetics. This Preferred Reporting Items for Sy...

Automated tick classification using deep learning and its associated challenges in citizen science.

Lyme borreliosis and tick-borne encephalitis significantly impact public health in Europe, transmitted primarily by endemic tick species. The recent i...

Machine learning models predict risk of lower extremity deep vein thrombosis in hospitalized patients with spontaneous intracerebral hemorrhage.

Lower extremity deep vein thrombosis is one of the important complications of spontaneous intracerebral hemorrhage. We aimed to develop a risk assessm...

How EEG preprocessing shapes decoding performance.

Electroencephalography (EEG) preprocessing varies widely between studies, but its impact on classification performance remains poorly understood. To a...

Bridging molecular and cellular neuroscience with proximity labeling technologies.

Proximity labeling (PL) techniques have advanced neuroscience by revealing the molecular interactions that govern neural circuits. From foundational t...

Sustainable analysis of COVID-19 Co-packaged paxlovid: exploring advanced sampling techniques and multivariate processing tools.

The drawbacks of random sampling not only hinder the development of more reliable and efficient methods but also weaken their accuracy, predictive abi...

Biomarkers and therapeutic strategies targeting microglia in neurodegenerative diseases: current status and future directions.

Recent advances in our understanding of non-cell-autonomous mechanisms in neurodegenerative diseases (NDDs) have highlighted microglial dysfunction as...

An investigation of multimodal EMG-EEG fusion strategies for upper-limb gesture classification.

. Upper-limb gesture identification is an important problem in the advancement of robotic prostheses. Prevailing research into classifying electromyog...

A transformer-based network with second-order pooling for motor imagery EEG classification.

. Electroencephalography (EEG) signals can reflect motor intention signals in the brain. In recent years, motor imagery (MI) based brain-computer inte...