Cardiovascular

Strokes

Latest AI and machine learning research in strokes for healthcare professionals.

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End-to-end deep learning patient level classification of affected territory of ischemic stroke patients in DW-MRI.

PURPOSE: To develop an end-to-end DL model for automated classification of affected territory in DWI...

Automated Segmentation of MRI White Matter Hyperintensities in 8421 Patients with Acute Ischemic Stroke.

BACKGROUND AND PURPOSE: To date, only a few small studies have attempted deep learning-based automat...

Advancing personalised care in atrial fibrillation and stroke: The potential impact of AI from prevention to rehabilitation.

Atrial fibrillation (AF) is a complex condition caused by various underlying pathophysiological diso...

Serum glial fibrillary acidic protein in acute stroke: feasibility to determine stroke-type, timeline and tissue-impact.

BACKGROUND: Interest is emerging regarding the role of blood biomarkers in acute stroke. The aim of ...

Design and validation of Withings ECG Software 2, a tiny neural network based algorithm for detection of atrial fibrillation.

BACKGROUND: Atrial Fibrillation (AF) is the most common form of arrhythmia in the world with a preva...

Machine learning evaluation of a hypertension screening program in a university workforce over five years.

The global prevalence of hypertension continues excessively elevated, especially among low- and midd...

Prediction of prolonged mechanical ventilation in the intensive care unit via machine learning: a COVID-19 perspective.

Early recognition of risk factors for prolonged mechanical ventilation (PMV) could allow for early c...

Effects of Robot-Assisted Gait Training on Balance and Fear of Falling in Patients With Stroke: A Randomized Controlled Clinical Trial.

OBJECTIVE: The aim of this study was compare the effects of combined training, which included robot-...

Deep learning-based segmentation of acute ischemic stroke MRI lesions and recurrence prediction within 1 year after discharge: A multicenter study.

OBJECTIVE: To explore the performance of deep learning-based segmentation of infarcted lesions in th...

Pathological Asymmetry-Guided Progressive Learning for Acute Ischemic Stroke Infarct Segmentation.

Quantitative infarct estimation is crucial for diagnosis, treatment and prognosis in acute ischemic ...

Identification of an immune-related gene panel for the diagnosis of pulmonary arterial hypertension using bioinformatics and machine learning.

OBJECTIVE: This study aimed to screen an immune-related gene (IRG) panel and develop a novel approac...

Machine learning-based diagnostic model for stroke in non-neurological intensive care unit patients with acute neurological manifestations.

Stroke is a neurological complication that can occur in patients admitted to the intensive care unit...

Telerehabilitation using a 2-D planar arm rehabilitation robot for hemiparetic stroke: a feasibility study of clinic-to-home exergaming therapy.

BACKGROUND: We evaluated the feasibility, safety, and efficacy of a 2D-planar robot for minimally su...

PhenoFlow: A Human-LLM Driven Visual Analytics System for Exploring Large and Complex Stroke Datasets.

Acute stroke demands prompt diagnosis and treatment to achieve optimal patient outcomes. However, th...

Predictive Factors Driving Positive Awake Test in Carotid Endarterectomy Using Machine Learning.

BACKGROUND: Positive neurologic awake testing during the carotid cross-clamping may be present in ar...

Enhancing Motor Imagery Classification with Residual Graph Convolutional Networks and Multi-Feature Fusion.

Stroke, an abrupt cerebrovascular ailment resulting in brain tissue damage, has prompted the adoptio...

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