Latest AI and machine learning research in strokes for healthcare professionals.
The rise of on-chip accelerators signifies a major shift in computing, driven by the growing demands of artificial intelligence (AI) and specialized applications. These accelerators have gained popularity due to their ability to substantially boost performance, cut energy usage, lower total cost of ownership (TCO), and promote sustainability. Intel's Advanced Matrix Extensions (AMX) is one such ...
Purpose: Enabling a comprehensive and robust assessment of carotid artery plaques in 3D through extraction and visualization of quantitative plaque parameters. These parameters have potential applications in stroke risk analysis, evaluation of therapy effectiveness, and plaque progression prediction. Methods: We propose a novel method for extracting a plaque mesh from 3D vessel wall segmentation...
With the increasing demand for storing images, traditional image compression methods face challenges in balancing the compressed size and image qual...
Mathematical reasoning in Large Language Models (LLMs) is often evaluated using benchmarks with limited numerical ranges, failing to reflect real-wo...
Ischaemic stroke, a leading cause of death and disability, critically relies on neuroimaging for characterising the anatomical pattern of injury. Di...
Fuzzy rule-based systems interpret data in low-dimensional domains, providing transparency and interpretability. In contrast, deep learning excels i...
Surprise Adequacy (SA) has been widely studied as a test adequacy metric that can effectively guide software engineers towards inputs that are more ...
Focal deficits in ischaemic stroke result from impaired perfusion downstream of a critical vascular occlusion. While parenchymal lesions are traditi...
Intrapleural enzyme therapy (IET) with tissue plasminogen activator (tPA) and DNase has been shown to reduce the need for surgical intervention for c...
Rehabilitation following a stroke faces challenges in offering customized treatment and attaining the best possible outcomes. The utilization of artif...
Stroke is globally a major cause of mortality and morbidity, and hence accurate and rapid diagnosis of stroke is valuable. Retinal fundus imaging re...
In this paper, we propose a privacy-enhancing technique leveraging an inherent property of automatic pedestrian detection algorithms, namely, that t...
Precise characterization of stroke lesions from MRI data has immense value in prognosticating clinical and cognitive outcomes following a stroke. Ma...
Electrical impedance tomography (EIT) is a non-invasive imaging method for recovering the internal conductivity of a physical body from electric bou...
The Wi-Fi technology (IEEE 802.11) was introduced in 1997. With the increasing use and deployment of such networks, their security has also attracte...
Effective fall risk assessment is critical for post-stroke patients. The present study proposes a novel, data-informed fall risk assessment method b...
Network control theory (NCT) has recently been utilized in neuroscience to facilitate our understanding of brain stimulation effects. A particularly...
Healthy brain networks usually show highly efficient information communication and self-sustained oscillation abilities. However, how the brain netw...
From Paleolithic cave paintings to Impressionism, human painting has evolved to depict increasingly complex and detailed scenes, conveying more nuan...
Ischemic stroke, caused by cerebral vessel occlusion, presents substantial challenges in medical imaging due to the variability and subtlety of stro...