Latest AI and machine learning research in neurology for healthcare professionals.
OBJECTIVE: To describe the use of Artificial Intelligence (AI) to automate the e-norms method, a tec...
The early detection of Alzheimer's Disease (AD) is thought to be important for effective interventio...
OBJECTIVE: The aim of this study was compare the effects of combined training, which included robot-...
In practice, collecting auxiliary labeled data with same feature space from multiple domains is diff...
Alzheimer's disease (AD) profoundly affects brain tissue and network structures. Analyzing the topol...
BACKGROUND: Treadmill based Robotic-Assisted Gait Training (t-RAGT) provides for automated locomotor...
Deep learning (DL) techniques are becoming more popular for diagnosing Parkinson's disease (PD) beca...
Much experimental evidence in neuroscience has suggested a division of higher visual processing into...
OBJECTIVE: To explore the performance of deep learning-based segmentation of infarcted lesions in th...
Portable, low-field magnetic resonance imaging (LF-MRI) of the brain may facilitate point-of-care as...
Quantitative infarct estimation is crucial for diagnosis, treatment and prognosis in acute ischemic ...
The electroencephalogram (EEG) signal has become a highly effective decoding target for emotion reco...
The motor imagery (MI) classification has been a prominent research topic in brain-computer interfac...
Humans show a remarkable ability in solving the cocktail party problem. Decoding auditory attention ...
Mounting evidence shows that Alzheimer's disease (AD) manifests the dysfunction of the brain network...
Cerebral Microbleeds (CMBs) are chronic deposits of small blood products in the brain tissues, which...
PURPOSE: While gait analysis is essential for assessing neuromotor disorders like cerebral palsy (CP...
BACKGROUND: Dementia rates are rising globally, impacting healthcare systems and society. The care o...
Brucellosis, a zoonotic disease caused by Brucella bacteria, poses significant risks to human, lives...
Motor imagery electroencephalography (MI-EEG) is usually used as a driving signal in neuro-rehabilit...
Closed-loop neuromodulation, especially using the phase of the electroencephalography (EEG) rhythm t...