Neurology

Robot-assisted spinal augmentation procedures: is it worth the increased effort?

PURPOSE: Spinal augmentation procedures (SAP) are standard procedures for vertebral compression fractures. Often, SAPs are carried out in a minimally invasive, percutaneous way. Certain anatomic conditions such as small pedicles or kyphotic deformities resulting from a significant collapse of the vertebral body might render the operation more difficult and increase the risk of complications. Thus,...

Does the Presence of Missing Data Affect the Performance of the SORG Machine-learning Algorithm for Patients With Spinal Metastasis? Development of an Internet Application Algorithm.

BACKGROUND: The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA) was developed to predict the survival of patients with spinal metastasis. The algorithm was successfully tested in five international institutions using 1101 patients from different continents. The incorporation of 18 prognostic factors strengthens its predictive ability but limits its clinical utility because s...

The clinical application of neuro-robot in the resection of epileptic foci: a novel method assisting epilepsy surgery.

During surgery for foci-related epilepsy, neurosurgeons face significant difficulties in identifying and resecting MRI-negative or deep-seated epilept...

An Attention-Aware Long Short-Term Memory-Like Spiking Neural Model for Sentiment Analysis.

LSTM-SNP model is a recently developed long short-term memory (LSTM) network, which is inspired from the mechanisms of spiking neural P (SNP) systems....

Machine learning algorithms for identifying predictive variables of mortality risk following dementia diagnosis: a longitudinal cohort study.

Machine learning (ML) could have advantages over traditional statistical models in identifying risk factors. Using ML algorithms, our objective was to...

Effect of Deep Learning Reconstruction on Evaluating Cervical Spinal Canal Stenosis With Computed Tomography.

OBJECTIVE: Magnetic resonance imaging (MRI) is commonly used to evaluate cervical spinal canal stenosis; however, some patients are ineligible for MRI...

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. Extra-ocular and bulbar muscles are most commonly aff...

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-assisted stereotactic lesioning versus epileptoge...

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 limitations of current assessment methods, which can be...

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-existing ones. AGPs have diverse applications in cancer,...

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, and most of them have a history of prodromal infec...

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 disorders in childhood. The incidence of this disease...

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 study, we assessed their impact on cerebrovascular flo...

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

To the Editor, Although postoperative pain associated with robot-assisted radical prostatectomy (RARP) is less than pain following the open technique,...

Explainable and Robust Deep Forests for EMG-Force Modeling.

Machine and deep learning techniques have received increasing attentions in estimating finger forces from high-density surface electromyography (HDsEM...

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 neuroimaging are either tested on unrepresentative p...

Clinical Outcomes of Pelvic Lymph Node Dissection Before Versus After Robot-Assisted Laparoscopic Radical Cystectomy.

The purpose of this study was to compare the clinical outcomes of bladder cancer patients treated with extended pelvic lymph node dissection (ePLND) ...

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 (PD) by showing reduced signals in the substantia ni...

Robot-assisted radical prostatectomy following holmium laser enucleation of the prostate: perioperative, functional, and oncological outcomes.

Robot-assisted radical prostatectomy with previous holmium laser enucleation of the prostate is challenging, and few studies have analyzed its periope...