Neurology

Keyhole Fenestration for Cerebrospinal Fluid Leaks in the Thoracic Spine: Quantification of Bone Removal and Microsurgical Anatomy.

BACKGROUND AND OBJECTIVE: A safe working trajectory is mandatory for spinal pathologies, especially in the midline, anterior to the spinal cord. For thoracic cerebrospinal fluid (CSF) leaks, we developed a minimally invasive keyhole fenestration. This study investigates the necessary bone removal for sufficient exposure of different leak types particularly regarding weight-bearing structures.

Robotic Microsurgery in Extremity Reconstruction - Experience With a Novel Robotic System.

Robotic systems have successfully been introduced into other surgical fields in the past. First attempts with different setups are made in the field of microsurgery. The Symani® Surgical System, a flexible platform consisting of two robotic arms, features motion scaling with tremor filtration to address the demands and complexity of microsurgery. Symani's NanoWrist Instruments are the world's sma...

Brain Topology Modeling With EEG-Graphs for Auditory Spatial Attention Detection.

OBJECTIVE: Despite recent advances, the decoding of auditory attention from brain signals remains a challenge. A key solution is the extraction of dis...

A Brain-Controlled Quadruped Robot: A Proof-of-Concept Demonstration.

Coupling brain-computer interfaces (BCIs) and robotic systems in the future can enable seamless personal assistant systems in everyday life, with the ...

Screening biomarkers for spinal cord injury using weighted gene co-expression network analysis and machine learning.

JOURNAL/nrgr/04.03/01300535-202412000-00028/figure1/v/2024-04-08T165401Z/r/image-tiff Immune changes and inflammatory responses have been identified a...

Metaphoric language in the differential diagnosis of epilepsy and psychogenic non-epileptic seizures: Time to move forward.

Conversation analysis (CA) to identify metaphoric language (ML) has been proposed as a tool for the differential diagnosis of epileptic (ES) and psych...

Cortico-cortical stimulation and robot-assisted therapy (CCS and RAT) for upper limb recovery after stroke: study protocol for a randomised controlled trial.

BACKGROUND: Since birth, during the exploration of the environment to interact with objects, we exploit both the motor and sensory components of the u...

High-Performance Hydrogel Sensors Enabled Multimodal and Accurate Human-Machine Interaction System for Active Rehabilitation.

Human-machine interaction (HMI) technology shows an important application prospect in rehabilitation medicine, but it is greatly limited by the unsati...

Deep learning applications in vascular dementia using neuroimaging.

PURPOSE OF REVIEW: Vascular dementia (VaD) is the second common cause of dementia after Alzheimer's disease, and deep learning has emerged as a critic...

Factors Associated With Nonunion After Cervical Fusion Surgery.

Background Bony fusion is a critical factor in the outcome of cervical spinal fusion surgery. While several factors have been proposed to affect bony ...

Bilateral upper limb robot-assisted rehabilitation improves upper limb motor function in stroke patients: a study based on quantitative EEG.

BACKGROUND: Upper limb dysfunction after stroke seriously affects quality of life. Bilateral training has proven helpful in recovery of upper limb mot...

Co-existence of Type 1 Diabetes Mellitus and Myasthenia Gravis: A Case Report and Review of the Literature.

BACKGROUND/OBJECTIVE: Type 1 diabetes (T1D) and myasthenia gravis (MG) are autoimmune conditions that rarely co-occur. Here, we report a child with MG...

scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles.

Many deep learning-based methods have been proposed to handle complex single-cell data. Deep learning approaches may also prove useful to jointly anal...

Brain age prediction using combined deep convolutional neural network and multi-layer perceptron algorithms.

The clinical applications of brain age prediction have expanded, particularly in anticipating the onset and prognosis of various neurodegenerative dis...

Using Explainable Artificial Intelligence to Obtain Efficient Seizure-Detection Models Based on Electroencephalography Signals.

Epilepsy is a condition that affects 50 million individuals globally, significantly impacting their quality of life. Epileptic seizures, a transient o...

A Short Review on the Impact of Artificial Intelligence in Diagnosis Diseases: Role of Radiomics In Neuro-Oncology.

Artificial Intelligence (AI) is rapidly transforming various aspects of healthcare, including the field of diagnostics and treatment of diseases. This...

Artificial intelligence in glaucoma detection using color fundus photographs.

PURPOSE: To explore the potential of artificial intelligence (AI) for glaucoma detection using deep learning algorithm and evaluate its accuracy for i...

Artificial intelligence-powered intraoperative nerve monitoring: a visionary method to reduce facial nerve palsy in parotid surgery: an editorial.

Electrophysiological brain imaging based on simulation-driven deep learning in the context of epilepsy.

Identifying the location, the spatial extent and the electrical activity of distributed brain sources in the context of epilepsy through ElectroEnceph...

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data.

Large omics datasets are becoming increasingly available for research into human health. This paper presents DeepOmicsAE, a workflow optimized for the...