BACKGROUND: Robotic rehabilitation, which provides a high-intensity, high-frequency therapy to improve neuroplasticity, is gaining traction. However, its effectiveness for upper extremity stroke rehabilitation remains uncertain. This study comprehens...
BACKGROUND: Predicting treated language improvement (TLI) and transfer to the untreated language (cross-language generalization, CLG) after speech-language therapy in bilingual individuals with poststroke aphasia is crucial for personalized treatment...
Artificial intelligence (AI) large language models (LLMs) now produce human-like general text and images. LLMs' ability to generate persuasive scientific essays that undergo evaluation under traditional peer review has not been systematically studied...
BACKGROUND: Cerebral small vessel disease is the most common pathology underlying vascular dementia. In small vessel disease, diffusion tensor imaging is more sensitive to white matter damage and better predicts dementia risk than conventional magnet...
BACKGROUND: Predicting stroke recurrence for individual patients is difficult, but individualized prediction may improve stroke survivors' engagement in self-care. We developed PRERISK: a statistical and machine learning classifier to predict individ...
BACKGROUND: Moyamoya disease (MMD) is a rare and complex pathological condition characterized by an abnormal collateral circulation network in the basal brain. The diagnosis of MMD and its progression is unpredictable and influenced by many factors. ...
BACKGROUND: Right to left shunt (RLS), including patent foramen ovale, is a recognized risk factor for stroke. RLS/patent foramen ovale diagnosis is made by transthoracic echocardiography (TTE), which is insensitive, transesophageal echocardiography,...
BACKGROUND: Predicting long-term clinical outcome based on the early acute ischemic stroke information is valuable for prognostication, resource management, clinical trials, and patient expectations. Current methods require subjective decisions about...