Latest AI and machine learning research in neurology for healthcare professionals.
Submandibular gland excision is generally performed through a transcervical approach, a safe procedure that, however, carries few neurological, functional and aesthetic drawbacks. Intraoral approach to the submandibular gland has been described many years ago but it has been newly proposed in recent years thanks to endoscope-assisted and robot-assisted surgical procedures. The main purpose of intr...
Early detection is crucial to prevent the progression of Alzheimer's disease (AD). Thus, specialists can begin preventive treatment as soon as possible. They demand fast and precise assessment in the diagnosis of AD in the earliest and hardest to detect stages. The main objective of this work is to develop a system that automatically detects the presence of the disease in sagittal magnetic resonan...
OBJECTIVE: Multiple sclerosis (MS) lesions are heterogeneous with regard to inflammation, demyelination, axonal injury, and neuronal loss. We previous...
: Innovative assistive technology can address aging-in-place and caregiving needs of individuals with Alzheimer's disease and related dementia (ADRD)....
People with tetraplegia resulting from spinal cord injury experience debilitating hand impairments that may lead to lifelong dependence on others to p...
BACKGROUND: Generally, brain-computer interfaces (BCIs) require calibration before usage to ensure efficient performance. Therefore, each BCI user has...
In this article we present a biologically inspired model of activation of memory items in a sequence. Our model produces two types of sequences, corre...
PURPOSE: To remove blood vessel shadows from optical coherence tomography (OCT) images of the optic nerve head (ONH).
Towards providing efficient human-robot interaction, surface electromyogram (EMG) signals have been widely adopted for the identification of different...
Understanding and classifying electromyogram (EMG) signals is of significance for dexterous prosthetic hand control, sign languages, grasp recognition...
AIM: This study aimed to use a convolutional neural network (CNN) to investigate the associations between the time of falling and multiple complicatin...
Chronic pain is highly prevalent and poorly controlled, of which the accurate underlying mechanisms need be further elucidated. Herbal drugs have been...
Metabolomics is a rapidly expanding technology that finds increasing application in a variety of fields, form metabolic disorders to cancer, from nutr...
BACKGROUND: Parkinson's disease (PD) ranks as the second most frequently occurring neurodegenerative disease. The precise pathogenic mechanism of this...
With the popularization of rehabilitation robots, it is necessary to develop quantitative motor function assessment methods for patients with a stroke...
The detection of recorded epileptic seizure activity in electroencephalogram (EEG) segments is crucial for the classification of seizures. Manual reco...
Quasi-stable electrical fields in the EEG, called microstates carry information on the dynamics of large scale brain networks. Using machine learning ...
State-of-the-art machine learning (ML) artificial intelligence methods are increasingly leveraged in clinical predictive modeling to provide clinical ...
In this paper, we applied a novel method for the detection of Alzheimer's disease (AD) based on a structural magnetic resonance imaging (sMRI) dataset...
Due to the difficulties and complications in the quantitative assessment of traumatic brain injury (TBI) and its increasing relevance in today's world...