Latest AI and machine learning research in neurology for healthcare professionals.
Understanding the neural mechanisms underlying the transitions between different states of consciousness is a fundamental challenge in neuroscience. Thus, we investigate the underlying drivers of changes during the resting-state dynamics of the human brain, as captured by functional magnetic resonance imaging (fMRI) across varying levels of consciousness (awake, light sedation, deep sedation, an...
Cerebral aneurysm rupture, leading to subarachnoid hemorrhage with a high mortality rate, disproportionately affects younger populations, resulting in a significant loss of productive life years. A significant proportion of these deaths is due to aneurysmal re-bleeding within the first three days following the initial bleed, prior to treatment. While early aneurysm treatment is recommended, ther...
BACKGROUND: This study aimed to investigate the effects of virtual reality (VR)-based robot therapy combined with task-oriented therapy on cerebral co...
Electroencephalogram (EEG) technology, particularly high-density EEG (HD EEG) devices, is widely used in fields such as neuroscience. HD EEG devices...
Those experiencing strokes, traumatic brain injuries, and drug complications can often end up hospitalized and diagnosed with coma or locked-in synd...
Advanced cognition can be extracted from the human brain using brain-computer interfaces. Integrating these interfaces with computer vision techniqu...
Recently, electroencephalography (EEG) signals have been actively incorporated to decode brain activity to visual or textual stimuli and achieve obj...
In this article, we consider the intersection of cognitive motor dissociation (CMD) and artificial intelligence (AI), hence when CMD meets AI. In cove...
Purpose To assess the performance of a local open-source large language model (LLM) in various information extraction tasks from real-life emergency b...
OBJECTIVES: To develop a machine learning model to accurately predict stroke risk based on demographic and clinical data. It also sought to identify t...
Cerebral small vessel disease (CSVD) is an important cause of stroke, cognitive impairment, and other diseases, and its early quantitative evaluation ...
BACKGROUND: Early medical attention after concussion may minimize symptom duration and burden; however, many concussions are undiagnosed or have a del...
Emotion recognition is of great significance for brain-computer interface and emotion computing, and EEG plays a key role in this field. However, the ...
Automatic detection of epilepsy plays a crucial role in diagnosing and treatment of patients, while most current methods rely on patient-specific mode...
In this study, we proposed a novel heterogeneous transfer learning approach named Focused Speech Feature Transfer Learning (FSFTL), aimed at enhancing...
The steady-state visual evoked potentials (SSVEP) based brain-computer interfaces (BCIs) require extensive training data for efficient classification,...
The structural Magnetic resonance imaging (sMRI) of spinal cord plays a significant role in the clinical diagnosis of Amyotrophic Lateral Sclerosis (A...
Neural activities in distinct brain regions variably contribute to the formation of motor imagery (MI). Utilizing the hidden contextual information ca...
Alzheimer's disease is the most common age-related problem and progresses in different stages, from cognitively normal to early mild cognitive impairm...
Deep learning models based on convolutional neural networks (CNNs) have been used to classify Alzheimer's disease or infer dementia severity from T1-w...