Cardiovascular

Strokes

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

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Machine learning for outcome prediction in patients with non-valvular atrial fibrillation from the GLORIA-AF registry.

Clinical risk scores that predict outcomes in patients with atrial fibrillation (AF) have modest pre...

Predictive modeling of preoperative acute heart failure in older adults with hypertension: a dual perspective of SHAP values and interaction analysis.

BACKGROUND: In older adults with hypertension, hip fractures accompanied by preoperative acute heart...

Multimodal Machine Learning for Stroke Prognosis and Diagnosis: A Systematic Review.

Stroke is a life-threatening medical condition that could lead to mortality or significant sensorimo...

Identification of novel hypertension biomarkers using explainable AI and metabolomics.

BACKGROUND: The global incidence of hypertension, a condition of elevated blood pressure, is rising ...

A cross-attention-based deep learning approach for predicting functional stroke outcomes using 4D CTP imaging and clinical metadata.

Acute ischemic stroke (AIS) remains a global health challenge, leading to long-term functional disab...

Brain Activation Pattern Caused by Soft Rehabilitation Glove and Virtual Reality Scenes: A Pilot fNIRS Study.

Clinical studies have proved significant improvements in hand motor function in stroke patients when...

SDS-Net: A Synchronized Dual-Stage Network for Predicting Patients Within 4.5-h Thrombolytic Treatment Window Using MRI.

Timely and precise identification of acute ischemic stroke (AIS) within 4.5 h is imperative for effe...

Impact of deep Learning-enhanced contrast on diagnostic accuracy in stroke CT angiography.

PURPOSE: To examine the impact of deep learning-augmented contrast enhancement on image quality and ...

Charting the growth through intelligence: A SWOC analysis on AI-assisted radiologic bone age estimation.

Bone age estimation (BAE) is based on skeletal maturity and degenerative process of the skeleton. Th...

Automated Extraction of Stroke Severity From Unstructured Electronic Health Records Using Natural Language Processing.

BACKGROUND: Multicenter electronic health records can support quality improvement and comparative ef...

A Study on Prevalence and Factors Affecting Hypertension in an Iranian Population: Results from the Fasa Cohort Study.

BACKGROUND: In recent years, hypertension has been one of the most important noncommunicable disease...

Predicting laboratory aspirin resistance in Chinese stroke patients using machine learning models by GP1BA polymorphism.

This study aims to use machine learning model to predict laboratory aspirin resistance (AR) in Chine...

Enhancing amide proton transfer imaging in ischemic stroke using a machine learning approach with partially synthetic data.

Amide proton transfer (APT) imaging, a technique sensitive to tissue pH, holds promise in the diagno...

Diagnostic performance of single-lead electrocardiograms for arterial hypertension diagnosis: a machine learning approach.

Awareness and early identification of hypertension is crucial in reducing the burden of cardiovascul...

Deep learning assists early-detection of hypertension-mediated heart change on ECG signals.

Arterial hypertension is a major risk factor for cardiovascular diseases. While cardiac ultrasound i...

Advancing Vascular Surgery: The Role Of Artificial Intelligence And Machine Learning In Managing Carotid Stenosis.

INTRODUCTION: Cardiovascular diseases affect 17.7 million people annually, worldwide. Carotid degene...

Comparative Scoping Review: Robot-Assisted Upper Limb Stroke Rehabilitation in Low- and Middle-Income Countries Versus High-Income Nations.

OBJECTIVE: To examine robotic interventions for upper limb rehabilitation poststroke, focusing on ge...

Evaluating retinal blood vessels for predicting white matter hyperintensities in ischemic stroke: A deep learning approach.

OBJECTIVE: This study aims to investigate whether a deep learning approach incorporating retinal blo...

The role of artificial intelligence in optimizing management of atrial fibrillation in acute ischemic stroke.

Atrial fibrillation (AF) is a severe condition associated with high morbidity and mortality, includi...

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