Neurology

A review of critical challenges in MI-BCI: From conventional to deep learning methods.

Brain-computer interfaces (BCIs) have achieved significant success in controlling external devices through the Electroencephalogram (EEG) signal processing. BCI-based Motor Imagery (MI) system bridges brain and external devices as communication tools to control, for example, wheelchair for people with disabilities, robotic control, and exoskeleton control. This success largely depends on the machi...

Urologic latency time during uroflow stop test with electromyography: an incontinence detector in rehabilitation after robotic radical prostatectomy.

BACKGROUND: Stress urinary incontinence (UI) is the most common presentation following robot-assisted radical prostatectomy (RARP), but a postoperative non-invasive and objective test is still lacking. To assess pelvic floor integrity after RARP, we recently proposed Uroflow Stop Test (UST) with surface electromyography (EMG).

Simplified approach to the medial internal iliac region using a uretero-hypogastric nerve fascia development procedure for extended pelvic lymph node dissection during robot-assisted radical prostatectomy for high-risk prostate cancer.

INTRODUCTION: Although several clinical guidelines for prostate cancer (PC) recommend extended pelvic lymph node dissection (ePLND) during radical pro...

A Deep CNN Framework for Neural Drive Estimation From HD-EMG Across Contraction Intensities and Joint Angles.

OBJECTIVE: Previous studies have demonstrated promising results in estimating the neural drive to muscles, the net output of all motoneurons that inne...

Research on Assistant Diagnosis of Fundus Optic Neuropathy Based on Deep Learning.

PURPOSE: The purpose of this study was to use the neural network to distinguish optic edema (ODE), and optic atrophy from normal fundus images and try...

Early diagnosis of Alzheimer's disease and mild cognitive impairment based on electroencephalography: From the perspective of event related potentials and deep learning.

Alzheimer's disease (AD), a neurodegenerative disorder characterized by progressive cognitive decline, is generally prevalent in elderly people with s...

CerebNet: A fast and reliable deep-learning pipeline for detailed cerebellum sub-segmentation.

Quantifying the volume of the cerebellum and its lobes is of profound interest in various neurodegenerative and acquired diseases. Especially for the ...

Deep Cellular Recurrent Network for Efficient Analysis of Time-Series Data With Spatial Information.

Efficient processing of large-scale time-series data is an intricate problem in machine learning. Conventional sensor signal processing pipelines with...

Ensemble Support Vector Recurrent Neural Network for Brain Signal Detection.

The brain-computer interface (BCI) P300 speller analyzes the P300 signals from the brain to achieve direct communication between humans and machines, ...

Automatic identification of early ischemic lesions on non-contrast CT with deep learning approach.

Early ischemic lesion on non-contrast computed tomogram (NCCT) in acute stroke can be subtle and need confirmation with magnetic resonance (MR) image ...

Deep Learning-Based Detection of Epileptiform Discharges for Self-Limited Epilepsy With Centrotemporal Spikes.

Centrotemporal spike-waves (CTSWs) are typical interictal epileptiform discharges (IEDs) observed in centrotemporal regions in self-limited epilepsy w...

NeuroConstruct: 3D Reconstruction and Visualization of Neurites in Optical Microscopy Brain Images.

We introduce NeuroConstruct, a novel end-to-end application for the segmentation, registration, and visualization of brain volumes imaged using wide-f...

Deep learning-based diagnosis of Alzheimer's disease using brain magnetic resonance images: an empirical study.

The limited accessibility of medical specialists for Alzheimer's disease (AD) can make obtaining an accurate diagnosis in a timely manner challenging ...

Graph Theoretical Analysis of EEG Functional Connectivity Patterns and Fusion with Physiological Signals for Emotion Recognition.

Emotion recognition is a key attribute for realizing advances in human-computer interaction, especially when using non-intrusive physiological sensors...

Association of nerve-sparing grading in robotic radical prostatectomy and trifecta outcome.

PURPOSE: To evaluate the neurovascular bundle preservation grades during robotic-assisted radical prostatectomy and compared to the trifecta combined ...

Prior optic neuritis detection on peripapillary ring scans using deep learning.

BACKGROUND: The diagnosis of multiple sclerosis (MS) requires demyelinating events that are disseminated in time and space. Peripapillary retinal nerv...

Artificial intelligence and treatment algorithms in spine surgery.

Artificial intelligence (AI) is a set of theories and techniques in which machines are used to simulate human intelligence with complex computer progr...

Brain Age Prediction/Classification through Recurrent Deep Learning with Electroencephalogram Recordings of Seizure Subjects.

With modern population growth and an increase in the average lifespan, more patients are becoming afflicted with neurodegenerative diseases such as de...

Robotic cochlear implantation in post-meningitis ossified cochlea.

AIM: To report the experience of an image-guided and navigation-based robot arm as an assistive surgical tool for cochlear implantation in a case with...

Completion of disconnective surgery for refractory epilepsy in pediatric patients using robot-assisted MRI-guided laser interstitial thermal therapy.

OBJECTIVE: Since 2007, the authors have performed 34 hemispherotomies and 17 posterior quadrant disconnections (temporoparietooccipital [TPO] disconne...