Strokes

Clinical prediction of aortic arch anatomy to guide stroke CT angiography protocols: A machine learning study.

BackgroundThe aortic arch (AA) influences catheter navigation during endovascular treatment (EVT) for acute ischemic stroke. Whether routine inclusion of the AA in stroke CT angiography (CTA) protocols is necessary remains debated, particularly in settings aiming to streamline imaging workflows.PurposeTo evaluate whether machine learning algorithms (MLAs) can use routinely available clinical and l...

Quantifying Innovation in Stroke: Large Language Model Bibliometric Analysis.

BACKGROUND: Thrombolysis and mechanical thrombectomy represent the most successful stroke innovations over the last 30 years. Quantifying innovation in stroke is essential for identifying productive research lines and prioritizing funding, but health care lacks validated methods for measuring innovation. OBJECTIVE: This study aimed to systematically evaluate the relationship between stroke-related...

Preoperative Neuroimaging Markers, Clinical Severity Measures, and Shunt Characteristics for Predicting Shunt Revision in Idiopathic Intracranial Hypertension: An Explainable Machine-Learning Study.

BACKGROUND AND PURPOSE: Surgical shunt placement is a common treatment for idiopathic intracranial hypertension (IIH) but is hampered by high revision...

A Streamlined 4-item Wolf Motor Function Test for Efficient Assessment of Upper Extremity Motor Function in Chronic Stroke Survivors.

BackgroundThe Wolf Motor Function Test (WMFT) is a well-recognized measure for assessing upper extremity motor function in stroke rehabilitation. Howe...

Machine learning for triage of strokes with large vessel occlusion using photoplethysmography biomarkers.

Objective.Large vessel occlusion (LVO) stroke presents a major challenge in clinical practice due to the potential for poor outcomes with delayed trea...

Deep learning in stroke therapeutics: drug repurposing and beyond.

INTRODUCTION: Deep learning is reshaping stroke research by accelerating drug repurposing amid heterogeneous pathology, narrow therapeutic windows, an...

Fibroblast-like cells accumulate late in human coronary atherosclerosis contributing to necrotic core formation.

AIMS: Proliferation of arterial smooth muscle cells (SMCs) and their modulation to alternative mesenchymal phenotypes is central to atherosclerotic le...

Insights into the interplay between stroke and depression through lipid metabolism-related diagnostic genes.

Stroke, a result of acute cerebrovascular disease that causes cerebral dysfunction, often coexists with depression or even major depressive disorder (...

Machine learning and SHAP values for predicting coronary artery disease risk in Xinjiang, China.

BACKGROUND: Accurate individual risk assessment is crucial for guiding and improving the prevention of atherosclerotic cardiovascular disease (ASCVD)....

Identifying and predicting gait stability metrics in people with stroke in uneven-surface walking using machine learning.

People with stroke (PwS) face increased fall risk on uneven surfaces; however, gait stability under such conditions remains unexplored. This study use...

AI-assisted multimodal assessment for right ventricular function from echocardiography predicts mortality in patients with pulmonary hypertension and right heart failure.

Right ventricular (RV) strain is an important factor in evaluating RV function. This study aimed to predict mortality in patients with pulmonary hyper...

Modeling Ischemic Stroke Pathological Dynamics via Continuous Fields and Vector Flow.

Precise localization of perfusion deficits in diffusion-weighted MRI (DWI) is critical for acute ischemic stroke management. However, existing deep le...

Comparative study of 11 machine learning algorithms for predicting recurrence risk after atrial fibrillation catheter ablation based on a real-world cohort: a retrospective study.

BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia worldwide, with catheter ablation being an effective yet recurrence-prone treatment...

Old Criteria, New Intelligence: The Evolution of ECG in Pulmonary Hypertension Diagnosis.

BACKGROUND: Pulmonary hypertension (PH) carries a significant mortality risk, highlighting the need for improved early detection strategies. This revi...

Initial diagnosis and management of acute ischemic stroke: recent update and future direction.

Acute ischemic stroke (AIS) outcomes depend critically on rapid, accurate early diagnosis in the emergency department. Traditional prehospital tools a...

Outcome Assessment in Stroke Using Multiparametric MRI: Integrating Infarct Location, Radiomics, and Global Brain Frailty.

BACKGROUND: Accurate assessment of 90-day functional outcomes after anterior circulation large vessel occlusion (LVO) stroke remains challenging. Conv...

YiQiFuMai ameliorates hypoperfusion-induced cerebral infarction by targeting the shear stress-PLBD1-glycolysis-angiogenesis axis.

BACKGROUND: Hypoperfusion-induced cerebral infarction remains a significant therapeutic challenge due to limited treatment options. Yiqi Fumai (YQFM),...

Predicting activities of daily living at discharge in stroke patients using rehabilitation robot training-induced functional connectivity.

BACKGROUND: Predicting activities of daily living (ADL) in stroke patients optimizes discharge planning, which relies on accurate functional assessmen...

The role of artificial intelligence in hypertension management.

PURPOSE OF REVIEW: Hypertension remains a leading modifiable risk factor for cardiovascular and renal conditions and dementia. Given its rising global...

The role of artificial intelligence in estimating stroke events in Moyamoya patients: A systematic review and meta-analysis of diagnostic test accuracy.

INTRODUCTION: Moyamoya disease (MMD) and syndrome (MMS) are rare cerebrovascular arteriopathies marked by progressive internal carotid stenosis, fragi...