Latest AI and machine learning research in neurology for healthcare professionals.
With the accelerating global population aging, establishing effective brain health assessment systems has emerged as a critical challenge in public health. Neuroimaging-based brain age prediction, serving as a potential biomarker for evaluating individual brain aging, has achieved remarkable breakthroughs in recent years. However, the accuracy of current brain age prediction models remains substan...
Carpal tunnel syndrome (CTS) is recognized as the most frequently encountered median nerve (MN) entrapment neuropathy, with a disproportionate burden in middle-aged and elderly individuals and in occupational groups with repetitive wrist use. Anatomically, CTS is characterized by compression of the median nerve within the confined space between the transverse carpal ligament and flexor tendons, an...
BACKGROUND: Spasticity is a common consequence of upper motor neuron syndrome, affecting approximately 42.6% of stroke patients and impairing quality ...
This study aims to develop a multimodal driver emotion recognition system that accurately identifies a driver's emotional state during the driving pro...
OBJECTIVES: Artificial Intelligence (AI) and Machine Learning (ML) are increasingly being applied in medical research, including studies on cerebral c...
With the rapid advancement of neuroimaging technologies, the development of deep learning-based models for the analysis of mental disorders has become...
OBJECTIVES: Epilepsy is a chronic neurological disorder characterized by recurrent seizures due to abnormal brain activity, which affects individuals'...
Accurate ischemic stroke lesion segmentation is useful to define the optimal reperfusion treatment and unveil the stroke etiology. Despite the importa...
Neuroimaging offers powerful evidence for the automated diagnosis of major depressive disorder (MDD). However, discrepancies across imaging modalities...
Multi-modal analysis can provide complementary information and significantly aid in the early diagnosis and intervention of Alzheimer's Disease (AD). ...
Ocular blood flow imaging techniques have become indispensable in current clinical practice because retinal vascular disturbances have been implicated...
Robot-assisted therapy, such as exoskeletons and soft robotics gloves, shows promise for stroke rehabilitation by improving upper limb function, altho...
BACKGROUND AND OBJECTIVES: Parkinson disease (PD) patients with motor complications are often considered for deep brain stimulation (DBS) surgery. Pre...
The intricate and efficient information processing of the human brain, driven by spiking neural interactions, has led to the development of spiking ne...
Alzheimer's disease (AD) is a neurodegenerative condition and the most common form of dementia. Recent developments in AD treatment call for robust di...
Traditionally, CT has been the go-to method for visualizing bone structures, while MRI has been preferred for assessing soft tissues, because structur...
BACKGROUND: Despite widespread use of intrapartum fetal monitoring, rates of fetal brain injury remain unchanged. Neonatal encephalopathy due to hypox...
Medical imaging plays a crucial role in the accurate diagnosis and prognosis of various medical conditions, with each modality offering unique and com...
Recent research studies in brain neural networks are highlighting the involvement of glial cells, in particular astrocytes, in synaptic modulation, me...
MicroRNAs (miRNAs) play a central role in gene regulation and have emerged as critical tools in disease diagnosis, therapy, and precision medicine. Ho...