Cardiovascular

Strokes

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

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Deep learning-based classification of speech disorder in stroke and hearing impairment.

BACKGROUND AND OBJECTIVE: Speech disorders can arise from various causes, including congenital condi...

The use of artificial intelligence to identify ophthalmic biomarkers in cardiovascular disease and stroke: a narrative review.

BACKGROUND: Cardiovascular disease (CVD) and stroke are among the leading causes of death worldwide.

Cyber security Enhancements with reinforcement learning: A zero-day vulnerabilityu identification perspective.

A zero-day vulnerability is a critical security weakness of software or hardware that has not yet be...

Automatic collateral quantification in acute ischemic stroke using U-net.

OBJECTIVES: To harness the U-Net deep learning framework for automated quantification of collateral ...

Emerging biomaterials and bio-nano interfaces in pulmonary hypertension therapy: transformative strategies for personalized treatment.

Pulmonary hypertension (PH) is still an aggressive and progressive illness with vascular remodeling ...

Optimizing Stroke Detection Using Evidential Networks and Uncertainty-Based Refinement.

Evaluating neurological impairments post-stroke is essential for assessing treatment efficacy and ma...

StackAHTPs: An explainable antihypertensive peptides identifier based on heterogeneous features and stacked learning approach.

Hypertension, often known as high blood pressure, is a major concern to millions of individuals glob...

Application of machine learning algorithms in predicting new onset hypertension: a study based on the China Health and Nutrition Survey.

BACKGROUND: Hypertension is a serious chronic disease that can significantly lead to various cardiov...

Predictive Value of Machine Learning Models for Cerebral Edema Risk in Stroke Patients: A Meta-Analysis.

INTRODUCTION: Stroke patients are at high risk of developing cerebral edema, which can have severe c...

Fair prediction of 2-year stroke risk in patients with atrial fibrillation.

OBJECTIVE: This study aims to develop machine learning models that provide both accurate and equitab...

Primary care research on hypertension: A bibliometric analysis using machine-learning.

Hypertension is one of the most important chronic diseases worldwide. Hypertension is a critical con...

Deep Learning and Single-Cell Sequencing Analyses Unveiling Key Molecular Features in the Progression of Carotid Atherosclerotic Plaque.

Rupture of advanced carotid atherosclerotic plaques increases the risk of ischaemic stroke, which ha...

Embolic Ischemic Cortical Stroke in a Young Flight Instructor with a Small Patent Foramen Ovale.

BACKGROUND: Stroke in young patients is frequently associated with a patent foramen ovale (PFO). Con...

Artificial intelligence classifies primary progressive aphasia from connected speech.

Neurodegenerative dementia syndromes, such as primary progressive aphasias (PPA), have traditionally...

Identification of fatty acid metabolism signature genes in patients with pulmonary arterial hypertension using WGCNA and machine learning.

OBJECTIVE: To investigate the signature genes of fatty acid metabolism and their association with im...

Effect of Upper Limb Repetitive Facilitative Exercise on Gait of Stroke Patients based on Artificial Intelligence and Computer Vision Evaluation.

OBJECTIVE: This study aims to assess how enhancing upper limb function on the affected side of strok...

Multimodal ischemic stroke recurrence prediction model based on the capsule neural network and support vector machine.

Ischemic stroke (IS) has a high recurrence rate. Machine learning (ML) models have been developed ba...

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