Latest AI and machine learning research in strokes for healthcare professionals.
Background Carotid plaque calcification is commonly interpreted as a marker of atherosclerotic burde...
Agentic research systems are emerging as a new paradigm for coordinating scientific workflows beyond...
Aphasia following stroke commonly produces systematic naming errors with characteristic profiles, bu...
Algorithmic fairness methods are increasingly used to identify and mitigate bias in machine learning...
Objective. To evaluate whether open-weight large language models (LLMs) can accurately extract clini...
Background: Hypertension is a modifiable risk factor for dementia, yet the comparative effectiveness...
Stroke is a leading cause of death and long-term disability worldwide, affecting approximately 15 mi...
Background: Frailty is common in acute ischemic stroke (AIS) and predicts poor outcomes, but is not ...
Purpose: EEG-based brain-machine interfaces (BMIs) may support assistive technologies for individual...
Large language models (LLMs) are increasingly used for automated quality control (QC) of radiology r...
Background Hypertension remains one of the most challenging healthcare problems in the community. It...
Importance: Machine-learning models for ischemic stroke risk prediction are rarely validated across ...
Multimodal large language models (MLLMs) extend large language models (LLMs) with visual perception,...
Acute ischemic stroke (AIS) is a leading cause of disability and death while effective treatment req...
Background: Corticospinal tract (CST) damage is a major cause of post-stroke motor deficits. However...
Restoring hand function remains a major challenge for individuals with motor impairments following s...
Self-supervised DINO models provide strong transferable visual representations, yet applying them di...
Objective: To construct and evaluate, in an exploratory manner, a pathophysiologic rationale link- i...
We built a multi-task pipeline for tennis stroke biomechanics from plain RGB video. On top of pose-b...
Personalized medicine in acute ischemic stroke requires moving beyond average treatment effects (ATE...
Background: Machine learning models for stroke mortality prediction typically treat each time horizo...