Cardiovascular

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

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Towards federated transfer learning in electrocardiogram signal analysis.

Modern methods in artificial intelligence perform very well on many healthcare datasets, at times ou...

A deep learning-based algorithm improves radiology residents' diagnoses of acute pulmonary embolism on CT pulmonary angiograms.

PURPOSE: To compare radiology residents' diagnostic performances to detect pulmonary emboli (PEs) on...

Robot-assisted vs laparoscopic bariatric procedures in super-obese patients: clinical and economic outcomes.

The increased operative time and costs represent the main limitations of robotic technology applicat...

Assessment of online information on robotic cardiac and thoracic surgery.

Online health resources are important for patients seeking perioperative information on robotic card...

Transferring a deep learning model from healthy subjects to stroke patients in a motor imagery brain-computer interface.

Motor imagery (MI) brain-computer interfaces (BCIs) based on electroencephalogram (EEG) have been de...

Deep learning-based diagnosis of aortic dissection using an electrocardiogram: Development, validation, and clinical implications of the AADE score.

BACKGROUND: Aortic dissection (AD) is frequently associated with abnormalities in electrocardiograph...

Incidence, Determinants, and Outcome of Contrast-induced Acute Kidney Injury following Percutaneous Coronary Intervention at a Tertiary Care Hospital.

Contrast-induced acute kidney injury (CI-AKI) after percutaneous coronary intervention (PCI) is the ...

Hyperpolarized Gas Imaging in Lung Diseases: Functional and Artificial Intelligence Perspective.

Pathophysiologic changes in lung diseases are often accompanied by changes in ventilation and gas ex...

Machine learning methods for developing a predictive model of the incidence of delirium in cardiac intensive care units.

INTRODUCTION AND OBJECTIVES: Delirium, recognized as a crucial prognostic factor in the cardiac inte...

Enriching Data Science and Health Care Education: Application and Impact of Synthetic Data Sets Through the Health Gym Project.

Large-scale medical data sets are vital for hands-on education in health data science but are often ...

Long-term results of ablation index guided atrial fibrillation ablation: insights after 5+ years of follow-up from the MPH AF Ablation Registry.

BACKGROUND: Catheter ablation (CA) for symptomatic atrial fibrillation (AF) offers the best outcomes...

Rehabilitation Evaluation of Upper Limb Motor Function for Stroke Patients Based on Belief Rule Base.

In the process of rehabilitation treatment for stroke patients, rehabilitation evaluation is a signi...

Time-domain heart rate dynamics in the prognosis of progressive atherosclerosis.

BACKGROUND AND AIM: The regular uptake of a high-fat diet (HFD) with changing lifestyle causes ather...

Deep Learning-Based Analysis of Aortic Morphology From Three-Dimensional MRI.

BACKGROUND: Quantification of aortic morphology plays an important role in the evaluation and follow...

A stepwise strategy integrating dynamic stress CT myocardial perfusion and deep learning-based FFR in the work-up of stable coronary artery disease.

OBJECTIVES: To validate a novel stepwise strategy in which computed tomography-derived fractional fl...

Recent developments in machine learning modeling methods for hypertension treatment.

Hypertension is the leading cause of cardiovascular complications. This review focuses on the advanc...

Perioperative Fluid and Vasopressor Therapy in 2050: From Experimental Medicine to Personalization Through Automation.

Intravenous (IV) fluids and vasopressor agents are key components of hemodynamic management. Since t...

Deep learning-based cerebral aneurysm segmentation and morphological analysis with three-dimensional rotational angiography.

BACKGROUND: The morphological assessment of cerebral aneurysms based on cerebral angiography is an e...

Quest for the ideal assessment of electrical ventricular dyssynchrony in cardiac resynchronization therapy.

This paper reviews the literature on assessing electrical dyssynchrony for patient selection in card...

Applications of AI in multi-modal imaging for cardiovascular disease.

Data for healthcare is diverse and includes many different modalities. Traditional approaches to Art...

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