Neurology

Assessing facial weakness in myasthenia gravis with facial recognition software and deep learning.

OBJECTIVE: Myasthenia gravis (MG) is an autoimmune disease leading to fatigable muscle weakness. Ext...

Protocol of a prospective multicenter randomized controlled trial of robot-assisted stereotactic lesioning in the treatment of focal drug-resistant epilepsy.

BACKGROUND: This protocol describes the design of a multicenter randomized controlled trial of robot...

Deep Learning for the Assessment of Facial Nerve Palsy: Opportunities and Challenges.

Automated evaluation of facial palsy using machine learning offers a promising solution to the limit...

Deep-AGP: Prediction of angiogenic protein by integrating two-dimensional convolutional neural network with discrete cosine transform.

Angiogenic proteins (AGPs) play a primary role in the formation of new blood vessels from pre-existi...

FDA-approved machine learning algorithms in neuroradiology: A systematic review of the current evidence for approval.

Over the past decade, machine learning (ML) and artificial intelligence (AI) have become increasingl...

Collaborative neurodynamic optimization for solving nonlinear equations.

A distributed optimization method for solving nonlinear equations with constraints is developed in t...

Development of a program to determine optimal settings for robot-assisted rehabilitation of the post-stroke paretic upper extremity: a simulation study.

Robot-assisted therapy can effectively treat upper extremity (UE) paralysis in patients who experien...

Robot-Guided Stereotactic Puncture and Drainage in the Treatment of Thalamic Abscess.

Brain abscess is rare in clinic, the reported incidence is only 0.4 to 0.90 per 100,000 population, ...

Label-free histological analysis of retrieved thrombi in acute ischemic stroke using optical diffraction tomography and deep learning.

For patients with acute ischemic stroke, histological quantification of thrombus composition provide...

Highly Bionic Neurotransmitter-Communicated Neurons Following Integrate-and-Fire Dynamics.

In biological neural networks, chemical communication follows the reversible integrate-and-fire (I&F...

Role of spinal anesthesia in robot-assisted radical prostatectomy: Gamble or opportunity?

To the Editor, Although postoperative pain associated with robot-assisted radical prostatectomy (RAR...

Deep learning phase error correction for cerebrovascular 4D flow MRI.

Background phase errors in 4D Flow MRI may negatively impact blood flow quantification. In this stud...

Detection of ADHD from EEG signals using new hybrid decomposition and deep learning techniques.

Attention deficit hyperactivity disorder (ADHD) is considered one of the most common psychiatric dis...

Explainable and Robust Deep Forests for EMG-Force Modeling.

Machine and deep learning techniques have received increasing attentions in estimating finger forces...

Nerve-sparing robot-assisted radical prostatectomy with the HUGO™ robot-assisted surgery system using the 'Aalst technique'.

Systematic Review of Artificial Intelligence for Abnormality Detection in High-volume Neuroimaging and Subgroup Meta-analysis for Intracranial Hemorrhage Detection.

PURPOSE: Most studies evaluating artificial intelligence (AI) models that detect abnormalities in ne...

Harnessing deep learning into hidden mutations of neurological disorders for therapeutic challenges.

The relevant study of transcriptome-wide variations and neurological disorders in the evolved field ...

Denoising approach with deep learning-based reconstruction for neuromelanin-sensitive MRI: image quality and diagnostic performance.

PURPOSE: Neuromelanin-sensitive MRI (NM-MRI) has proven useful for diagnosing Parkinson's disease (P...

The neuromechanics of animal locomotion: From biology to robotics and back.

Robotics and neuroscience are sister disciplines that both aim to understand how agile, efficient, a...

BrainS: Customized multi-core embedded multiple scale neuromorphic system.

Research on modeling and mechanisms of the brain remains the most urgent and challenging task. The c...

The neuroconnectionist research programme.

Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to model behav...