Neurology

Does the alternating timing of rTMS combined with soft-hand rehabilitation robot affect the recovery of hand function in patients after stroke? A study protocol for a multicentre randomised controlled trial.

INTRODUCTION: Combining repetitive transcranial magnetic stimulation (rTMS) with robotic training could result in more significant improvements in motor function than either treatment alone. The efficacy of this combination may depend on the sequencing of the interventions. However, few studies have explored the possibility of interleaving or alternating between the two treatment modalities within...

SeizyML: An Application for Semi-Automated Seizure Detection Using Interpretable Machine Learning Models.

Despite the vast number of publications reporting seizures and the reliance of the field on accurate seizure detection, there is a lack of open-source software tools in the scientific community for automating seizure detection based on electrographic recordings. Researchers instead rely on manual curation of seizure detection that is highly laborious, inefficient and can be error prone and heavily...

Applying machine learning to high-dimensional proteomics datasets for the identification of Alzheimer's disease biomarkers.

PURPOSE: This study explores the application of machine learning to high-dimensional proteomics datasets for identifying Alzheimer's disease (AD) biom...

A Surface-Enhanced Raman Spectroscopy Platform Integrating Dual Signal Enhancement and Machine Learning for Rapid Detection of Veterinary Drug Residues in Meat Products.

The detection and quantification of veterinary drug residues in meat remain a significant challenge due to the complex background interference inheren...

Artificial intelligence-driven 3D MRI of lumbosacral nerve root anomalies: accuracy, incidence, and clinical utility.

PURPOSE: Lumbosacral nerve root anomalies are relatively rare but can be a risk factor for intraoperative nerve injury. However, it is often difficult...

Machine-learning models for the prediction of ideal surgical outcomes in patients with adult spinal deformity.

AIMS: Adult spinal deformity (ASD) surgery can reduce pain and disability. However, the actual surgical efficacy of ASD in doing so is far from desira...

Pre-trained convolutional neural networks identify Parkinson's disease from spectrogram images of voice samples.

Machine learning approaches including deep learning models have shown promising performance in the automatic detection of Parkinson's disease. These a...

Predictive stress analysis in simplified spinal disc model using physics-informed neural networks.

This study develops a physics-informed neural network (PINN) model to predict stress distribution in a simplified spinal disc structure. The model inc...

Denoising Diffusion Probabilistic Model to Simulate Contrast-enhanced spinal MRI of Spinal Tumors: A Multi-Center Study.

RATIONALE AND OBJECTIVES: To generate virtual T1 contrast-enhanced (T1CE) sequences from plain spinal MRI sequences using the denoising diffusion prob...

Deep Learning-Assisted Diagnosis of Malignant Cerebral Edema Following Endovascular Thrombectomy.

BACKGROUND: Malignant cerebral edema (MCE) is a significant complication following endovascular thrombectomy (EVT) in the treatment of acute ischemic ...

A hybrid network based on multi-scale convolutional neural network and bidirectional gated recurrent unit for EEG denoising.

Electroencephalogram (EEG) signals are time series data containing abundant brain information. However, EEG frequently contains various artifacts, suc...

Effects of robot-assisted gait training within 1 week after stroke onset on degree of gait independence in individuals with hemiparesis: a propensity score-matched analysis in a single-center cohort study.

BACKGROUND: Robot-assisted gait training (RAGT) is an effective method for treating gait disorders in individuals with stroke. However, no previous st...

Clinical Application of Artificial Intelligence Preoperative Planning System Combined with Expert Database Retrieval in Complex Revision Hip Surgery.

Accurate preoperative planning in revision hip arthroplasty is crucial for achieving successful outcomes. To enhance the intuitive evaluation of aceta...

Enhanced U-Net for Infant Brain MRI Segmentation: A (2+1)D Convolutional Approach.

BACKGROUND: Infant brain tissue segmentation from MRI data is a critical task in medical imaging, particularly challenging due to the evolving nature ...

Nonlocal models in biology and life sciences: Sources, developments, and applications.

Mathematical modeling is one of the fundamental techniques for understanding biophysical mechanisms in developmental biology. It helps researchers to ...

Machine learning analysis of cortical activity in visual associative learning tasks with differing stimulus complexity.

Associative learning tests are cognitive assessments that evaluate the ability of individuals to learn and remember relationships between pairs of sti...

Neurofind: using deep learning to make individualised inferences in brain-based disorders.

Within precision psychiatry, there is a growing interest in normative models given their ability to parse heterogeneity. While they are intuitive and ...

Improving ALS detection and cognitive impairment stratification with attention-enhanced deep learning models.

Amyotrophic lateral sclerosis (ALS) is a fatal neurological disease marked by motor deterioration and cognitive decline. Early diagnosis is challengin...

Machine learning analysis of gene expression profiles of pyroptosis-related differentially expressed genes in ischemic stroke revealed potential targets for drug repurposing.

The relationship between ischemic stroke (IS) and pyroptosis centers on the inflammatory response elicited by cerebral tissue damage during an ischemi...

Machine Learning Methods for Classifying Multiple Sclerosis and Alzheimer's Disease Using Genomic Data.

Complex diseases pose challenges in prediction due to their multifactorial and polygenic nature. This study employed machine learning (ML) to analyze ...