Latest AI and machine learning research in neurology for healthcare professionals.
Human-administered clinical scales are commonly used for quantifying motor performance and determining the course of therapy in post-stroke individuals. Computerized methods aim to improve consistency, resolution and duration of patients' evaluation. The objective of this study was to test the validity of computerized square-drawing test (DT) for assessment of shoulder and elbow function by using ...
The apparent unpredictability of epileptic seizures has a major impact in the quality of life of people with pharmacologically resistant seizures. Here, we present initial results and a proof-of-concept of how focal seizures can be predicted early in advance based on intracortical signals recorded from small neocortical patches away from identified seizure onset areas. We show that machine learnin...
The conservative transoral approach to hilo-parenchymal submandibular stones has been proposed as an alternative to traditional sialadenectomy. The ma...
Each brain hemisphere is dominant for certain functions such as speech. The determination of speech laterality prior to surgery is of paramount import...
Toxic misfolded proteins potentially underly many neurodegenerative diseases, but individual targets which regulate these proteins and their downstrea...
While convolutional neural network (CNN) has been demonstrating powerful ability to learn hierarchical spatial features from medical images, it is sti...
Accurate prediction of disease trajectories is critical for early identification and timely treatment of patients at risk. Conventional methods in sur...
Epilepsy is one of the world's most common neurological diseases. Early prediction of the incoming seizures has a great influence on epileptic patient...
The diagnosis of depression almost exclusively depends on doctor-patient communication and scale analysis, which have the obvious disadvantages such a...
Artificial intelligence, specifically machine learning, has found numerous applications in computer-aided diagnostics, monitoring and management of ne...
In recent studies, neuroanatomical volume and shape asymmetries have been seen during the course of Alzheimer's Disease (AD) and could potentially be ...
OBJECTIVE: Lipid peroxidation constitutes a molecular mechanism involved in early Alzheimer Disease (AD) stages, and artificial neural network (ANN) a...
Multi-channel EEG data are usually necessary for spatial pattern identification in motor imagery (MI)-based brain computer interfaces (BCIs). To some ...
As the incidence of senile dementia continues to increase, researches on Alzheimer's disease (AD) have become more and more important. Several studies...
BACKGROUND: Finding interictal epileptiform discharges (IEDs) in the EEG is a part of diagnosing epilepsy. Automated software for annotating EEGs of p...
. In a previous study, we showed a new EEG processing methodology called Multi-Scale Ranked Organizing Map/Implicit Function As Squashing Time (MS-ROM...
Robot-assisted gait training following acute stroke could allow patients with severe disability to receive a high dosage and intensity of gait trainin...
OBJECTIVES: has long been used in folk medicine to treat diseases including fever, headache, burns, constipation, gut pains, and inflammation. Nitric...
There have been different efforts to predict epileptic seizures and most of them are based on the analysis of electroencephalography (EEG) signals; ho...
Complex dendrites in general present formidable challenges to understanding neuronal information processing. To circumvent the difficulty, a prevalent...