Latest AI and machine learning research in neurology for healthcare professionals.
BACKGROUND: Transcarotid artery revascularization (TCAR) has assumed a significant role in the surgical treatment of extracranial carotid occlusive disease in current practice. Yet, TCAR specific factors which predispose to periprocedural stroke remain poorly characterized. The purpose of this analysis was to identify factors which may inherently predispose to adverse outcomes in patients undergoi...
BACKGROUND: The role of lactate metabolism in ischemic stroke (IS) remains incompletely understood. This study aimed to characterize lactate-related transcriptomic profiles in IS to identify novel diagnostic biomarkers. METHODS: Gene co-expression network analysis and machine learning were used to identify core lactate metabolism-related genes from public transcriptomic datasets and validate them ...
Sleep supports cardiovascular, metabolic, neurologic, and psychological health. Beyond duration, circadian alignment is crucial because regular sleep,...
In the past few years, Hand Gesture Recognition (HGR) utilizing EMG data has gained significant attention for improving human-machine interaction. How...
In this study, we present SpineDL, an open-source deep learning (DL) approach for neuron and anatomical structure segmentation of the spinal cord in f...
Rare diseases impose a disproportionate clinical burden, and yet therapeutic progress is hindered by small cohorts, biological heterogeneity, and limi...
Gene delivery for neurodegenerative cerebral disorders faces formidable structural and practical challenges. The blood-brain, blood- cerebrospinal flu...
Technology is transforming rehabilitative medicine by enhancing accessibility and personalisation. Robot-assisted rehabilitation uses robotic systems ...
BACKGROUND: Annually, stroke affects over 15 million people globally. Early intervention is critical in the management of stroke. However, the "golden...
Vitamin B12 is essential for neural function, red blood cell formation, and DNA synthesis, yet its deficiency persists as a global health burden drivi...
Epilepsy manifests as a chronic neurological condition marked by recurrent seizures. Recent advances in computational analysis of Electroencephalograp...
Artificial intelligence is increasingly applied in early drug discovery to accelerate hit identification and reduce costs. In this study, we implement...
Explainable Artificial Intelligence (XAI) is gaining popularity in early diagnosis and monitoring of dementia. Herein, we recommend the incorporation ...
Accurate estimation of long-range directed connectivity remains a critical challenge in recurrent neural network design due to vanishing gradients ove...
Cardiovascular diseases (CVDs) continue to be a significant public health burden and public health emergency in the world, underscoring the importance...
We introduce a quantitative pipeline for region-level explanations of an Alzheimer's prediction model using four post hoc explainable AI (XAI) methods...
OBJECTIVE: To compare robotic body weight supported treadmill training (RBWSTT), overground robotic exoskeleton training (ORET), and conventional phys...
BACKGROUND: Patients' engagement plays a crucial role in the effectiveness of robot-assisted gait training (RAGT), particularly in paediatric neuroreh...
BACKGROUND: Despite increased awareness of diversity and inclusion in neurointerventional surgery, the representation of women in neurointerventional ...
BACKGROUND: Magnetic resonance imaging (MRI) is critical for acute stroke triage, but it is time-consuming and often requires contrast injection for p...