Neurology

Classification of needle-EMG resting potentials by machine learning.

INTRODUCTION: The diagnostic importance of audio signal characteristics in needle electromyography (EMG) is well established. Given the recent advent of audio-sound identification by artificial intelligence, we hypothesized that the extraction of characteristic resting EMG signals and application of machine learning algorithms could help classify various EMG discharges.

Automated classification of Alzheimer's disease and mild cognitive impairment using a single MRI and deep neural networks.

We built and validated a deep learning algorithm predicting the individual diagnosis of Alzheimer's disease (AD) and mild cognitive impairment who will convert to AD (c-MCI) based on a single cross-sectional brain structural MRI scan. Convolutional neural networks (CNNs) were applied on 3D T1-weighted images from ADNI and subjects recruited at our Institute (407 healthy controls [HC], 418 AD, 280 ...

Sensorimotor Robotic Measures of tDCS- and HD-tDCS-Enhanced Motor Learning in Children.

Transcranial direct-current stimulation (tDCS) enhances motor learning in adults. We have demonstrated that anodal tDCS and high-definition (HD) tDCS ...

Degradation of TRPML1 in Neurons Reduces Neuron Survival in Transient Global Cerebral Ischemia.

Postcardiac arrest syndrome yields poor neurological outcomes, but the mechanisms underlying this condition remain poorly understood. Autophagy plays ...

On medical application of neural networks trained with various types of data.

Neural networks have garnered attention over the past few years. A neural network is a typical model of machine learning that is used to identify visu...

From research to clinic: A sensor reduction method for high-density EEG neurofeedback systems.

OBJECTIVE: To accurately deliver a source-estimated neurofeedback (NF) signal developed on a 128-sensors EEG system on a reduced 32-sensors EEG system...

Cubital Tunnel Decompression: Equivalent Outcome Scores when Procedure Performed with Local versus General Anesthetic.

Ulnar nerve compression at the cubital tunnel is the second commonest upper limb neuropathy. Unlike carpal tunnel surgery, most of decompression proc...

Alterations in muscle activation patterns during robot-assisted bilateral training: A pilot study.

Robot-assisted bilateral training is being developed as a new rehabilitation approach for stroke patients. However, there is still a lack of understan...

Antemortem CSF A42/A40 ratio predicts Alzheimer's disease pathology better than A42 in rapidly progressive dementias.

OBJECTIVE: Despite the critical importance of pathologically confirmed samples for biomarker validation, only a few studies have correlated CSF A42 va...

Recognition of Emotions Using Multichannel EEG Data and DBN-GC-Based Ensemble Deep Learning Framework.

Fusing multichannel neurophysiological signals to recognize human emotion states becomes increasingly attractive. The conventional methods ignore the ...

Morphometric analysis of peripheral myelinated nerve fibers through deep learning.

Irrespective of initial causes of neurological diseases, these disorders usually exhibit two key pathological changes-axonal loss or demyelination or ...

Probiotic and selenium co-supplementation, and the effects on clinical, metabolic and genetic status in Alzheimer's disease: A randomized, double-blind, controlled trial.

BACKGROUND AND AIMS: Combined probiotic and selenium supplementation may improve Alzheimer's disease (AD) by correcting metabolic abnormalities, and a...

Automatic seizure detection using three-dimensional CNN based on multi-channel EEG.

BACKGROUND: Automated seizure detection from clinical EEG data can reduce the diagnosis time and facilitate targeting treatment for epileptic patients...

Development and flight performance of a biologically-inspired tailless flapping-wing micro air vehicle with wing stroke plane modulation.

The tailless flapping-wing micro air vehicle (FW-MAV) is one of the most challenging problems in flapping-wing design due to its lack of tail for inhe...

Correlation-Aware Sparse and Low-Rank Constrained Multi-Task Learning for Longitudinal Analysis of Alzheimer's Disease.

Alzheimer's disease (AD), as a severe neurodegenerative disease, is now attracting more and more researchers' attention in the healthcare. With the de...

Pet robot intervention for people with dementia: A systematic review and meta-analysis of randomized controlled trials.

This study aims to systematically evaluate the efficacy of Pet robot intervention (PRI) for people with dementia. Two waves of electronic searches of ...

Automated glaucoma diagnosis using bit-plane slicing and local binary pattern techniques.

BACKGROUND AND OBJECTIVE: Glaucoma is a ocular disorder which causes irreversible damage to the retinal nerve fibers. The diagnosis of glaucoma is imp...

Shared Decision-Making Ontology for a Healthcare Team Executing a Workflow, an Instantiation for Metastatic Spinal Cord Compression Management.

Regardless of potential benefits and better outcomes, adoption of shared decision-making between a patient and providers involved in his/her care is s...

Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease.

Parkinson's Disease (PD) is one of the most prevalent neurodegenerative diseases that affects tens of millions of Americans. PD is highly progressive ...

Visual Explanations From Deep 3D Convolutional Neural Networks for Alzheimer's Disease Classification.

We develop three efficient approaches for generating visual explanations from 3D convolutional neural networks (3D-CNNs) for Alzheimer's disease class...