Latest AI and machine learning research in strokes for healthcare professionals.
Background: Current medical large language model (LLM) evaluations largely rely on small collections...
Machine unlearning for text-to-image diffusion models aims to selectively remove undesirable concept...
Vision-language models (VLMs) are increasingly used in settings where sensitivity to low-level image...
Vision-Language Models (VLMs) are increasingly used in clinical diagnostics, yet their robustness to...
Stroke-associated pneumonia (SAP) is a common, severe complication in acute ischemic stroke (AIS) pa...
The integration of Large Language Models (LLMs) into clinical decision support is critically obstruc...
In stroke-based rendering, search methods often get trapped in local minima due to discrete stroke p...
This work introduces a new approach to automatic oil painting that emphasizes the creation of dynami...
Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia worldwide and is strongly associat...
Background: The 2017 American College of Cardiology/American Heart Association (ACC/AHA) guideline l...
Cells that appear transcriptionally identical can maintain vastly different functions or fate, an en...
Background: Current risk assessment tools for guiding direct oral anticoagulant (DOAC) therapy for p...
Accurate sleep staging is essential for diagnosing OSA and hypopnea in stroke patients. Although PSG...
Sleep disturbances lead to risk for cardiovascular (CV), metabolic, and neurological diseases. While...
Retinal fundus imaging enables low-cost and scalable hypertension (HTN) screening, but HTN-related r...
Background: Prospective stroke registries have advanced our understanding of cerebrovascular disease...
Stroke is a leading cause of mortality and morbidity worldwide. MRI-visible perivascular spaces (PVS...
Background Hemorrhagic transformation (HT) after endovascular thrombectomy (EVT) is a principal dete...
Early identification of individuals at risk of stroke remains a major clinical challenge, as prodrom...
Purpose: To develop a data-efficient strategy for accelerated MRI reconstruction with Diffusion Prob...
Chronic diseases are long-lasting conditions that require lifelong medical attention. Using big EMR ...