Neurology

A randomized controlled trial on the effects induced by robot-assisted and usual-care rehabilitation on upper limb muscle synergies in post-stroke subjects.

Muscle synergies are hypothesized to reflect connections among motoneurons in the spinal cord activated by central commands and sensory feedback. Robotic rehabilitation of upper limb in post-stroke subjects has shown promising results in terms of improvement of arm function and motor control achieved by reassembling muscle synergies into a set more similar to that of healthy people. However, in st...

StoCast: Stochastic Disease Forecasting With Progression Uncertainty.

Forecasting patients' disease progressions with rich longitudinal clinical data has drawn much attention in recent years due to its impactful application in healthcare and the medical field. Researchers have tackled this problem by leveraging traditional machine learning, statistical techniques and deep learning based models. However, existing methods suffer from either deterministic internal stru...

Epidemiological Surveillance of the Impact of the COVID-19 Pandemic on Stroke Care Using Artificial Intelligence.

BACKGROUND AND PURPOSE: The degree to which the coronavirus disease 2019 (COVID-19) pandemic has affected systems of care, in particular, those for ti...

Effects of Robotic Neurorehabilitation on Body Representation in Individuals with Stroke: A Preliminary Study Focusing on an EEG-Based Approach.

Patients with stroke can experience a drastic change in their body representation (BR), beyond the physical and psychological consequences of stroke i...

Motor Recovery: How Rehabilitation Techniques and Technologies Can Enhance Recovery and Neuroplasticity.

There are now a large number of technological and methodological approaches to the rehabilitation of motor function after stroke. It is important to e...

Clinical presentation of COVID-19 - a model derived by a machine learning algorithm.

COVID-19 pandemic has flooded all triage stations, making it difficult to carefully select those most likely infected. Data on total patients tested, ...

Application Prospect of Artificial Intelligence in Rehabilitation and Management of Myasthenia Gravis.

Myasthenia gravis (MG) is a chronic autoimmune disease of the nervous system, which is still incurable. In recent years, with the progress of immunosu...

Privacy-Preserving Deep Speaker Separation for Smartphone-Based Passive Speech Assessment.

Smartphones can be used to passively assess and monitor patients' speech impairments caused by ailments such as Parkinson's disease, Traumatic Brain ...

Robot-Based Assessment of HIV-Related Motor and Cognitive Impairment for Neurorehabilitation.

There is a pressing need for strategies to slow or treat the progression of functional decline in people living with HIV. This paper explores a novel ...

Comparison of clinical outcomes and accuracy of electrode placement between robot-assisted and conventional deep brain stimulation of the subthalamic nucleus: a single-center study.

BACKGROUND: Several surgical methods are used for deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD). This stud...

Alzheimer's disease detection using depthwise separable convolutional neural networks.

To diagnose Alzheimer's disease (AD), neuroimaging methods such as magnetic resonance imaging have been employed. Recent progress in computer vision w...

The Influence of EMG-Triggered Robotic Movement on Walking, Muscle Force and Spasticity after an Ischemic Stroke.

: Application of the EMG-driven robotic training in everyday therapeutic processes is a modern and innovative form of neurorehabilitation among patien...

Investigating the relationship between the SNCA gene and cognitive abilities in idiopathic Parkinson's disease using machine learning.

Cognitive impairments are prevalent in Parkinson's disease (PD), but the underlying mechanisms of their development are unknown. In this study, we aim...

Examining the Utility of the DESCARTE Model for Case Study Research.

The DESCARTE model aims to guide health care researchers on the design, conduct, and reporting of case studies. The current article critically apprais...

External validation of automated focal cortical dysplasia detection using morphometric analysis.

OBJECTIVE: Focal cortical dysplasias (FCDs) are a common cause of drug-resistant focal epilepsy but frequently remain undetected by conventional magne...

ASO Author Reflections: "Modified Bascule Method" during Robot-Assisted Minimally Invasive Esophagectomy Has Potential to Decrease Recurrent Laryngeal Nerve Palsy.

Diffusion histology imaging differentiates distinct pediatric brain tumor histology.

High-grade pediatric brain tumors exhibit the highest cancer mortality rates in children. While conventional MRI has been widely adopted for examining...

Prediction of cerebral perfusion pressure during CPR using electroencephalogram in a swine model of ventricular fibrillation.

BACKGROUND: Measuring the quality of cardiopulmonary resuscitation (CPR) is important for improving outcomes in cardiac arrest. Cerebral perfusion pre...

Prediction Model of Amyotrophic Lateral Sclerosis by Deep Learning with Patient Induced Pluripotent Stem Cells.

In amyotrophic lateral sclerosis (ALS), early diagnosis is essential for both current and potential treatments. To find a supportive approach for the ...

Deep learning based automatic diagnosis of first-episode psychosis, bipolar disorder and healthy controls.

Neuroimaging data driven machine learning based predictive modeling and pattern recognition has been attracted strongly attention in biomedical scienc...