Cardiovascular

Myocardial Infarction

Latest AI and machine learning research in myocardial infarction for healthcare professionals.

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Premature ventricular contraction detection combining deep neural networks and rules inference.

Premature ventricular contraction (PVC), which is a common form of cardiac arrhythmia caused by ecto...

Infrastructure and distributed learning methodology for privacy-preserving multi-centric rapid learning health care: euroCAT.

Machine learning applications for personalized medicine are highly dependent on access to sufficient...

Robot-assisted thoracoscopic lobectomy as treatment of a giant bulla.

BACKGROUND: A bulla is a marked enlarged space within the parenchyma of the lung. Bullae may cause d...

Patient-Specific Deep Architectural Model for ECG Classification.

Heartbeat classification is a crucial step for arrhythmia diagnosis during electrocardiographic (ECG...

Prediction of high on-treatment platelet reactivity in clopidogrel-treated patients with acute coronary syndromes.

BACKGROUND: About 40% of clopidogrel-treated patients display high platelet reactivity (HPR). Altern...

Ventricular Fibrillation and Tachycardia detection from surface ECG using time-frequency representation images as input dataset for machine learning.

BACKGROUND AND OBJECTIVE: To safely select the proper therapy for Ventricullar Fibrillation (VF) is ...

Automated diagnosis of congestive heart failure using dual tree complex wavelet transform and statistical features extracted from 2s of ECG signals.

Identification of alarming features in the electrocardiogram (ECG) signal is extremely significant f...

Reducing false arrhythmia alarm rates using robust heart rate estimation and cost-sensitive support vector machines.

To lessen the rate of false critical arrhythmia alarms, we used robust heart rate estimation and cos...

Highly sensitive amperometric detection of cardiac troponin I using sandwich aptamers and screen-printed carbon electrodes.

In this study, we developed a sandwich aptamer-based screen-printed carbon electrode (SPCE) using ch...

Impact of robotics and a suspended lead suit on physician radiation exposure during percutaneous coronary intervention.

BACKGROUND: Reports of left-sided brain malignancies among interventional cardiologists have heighte...

Long-Term Percutaneous Coronary Intervention Outcomes of Patients with Chronic Kidney Disease in the Era of Second-Generation Drug-Eluting Stents.

BACKGROUND: The following registry (Katowice-Zabrze retrospective registry) aimed to assess the infl...

Impact of vitamin D status on statin-induced myopathy.

INTRODUCTION: There is a multitude of evidence supporting the benefit of statin use in cardiovascula...

A novel algorithm for ventricular arrhythmia classification using a fuzzy logic approach.

In the present study, it has been shown that an unnecessary implantable cardioverter-defibrillator (...

Cardiac Biomarkers of Low Cardiac Output Syndrome in the Postoperative Period After Congenital Heart Disease Surgery in Children.

INTRODUCTION AND OBJECTIVES: To assess the predictive value of atrial natriuretic peptide, β-type na...

MAG-DPA curbs inflammatory biomarkers and pharmacological reactivity in cytokine-triggered hyperresponsive airway models.

Bronchial inflammation contributes to a sustained elevation of airway hyperresponsiveness (AHR) in a...

A novel machine learning-enabled framework for instantaneous heart rate monitoring from motion-artifact-corrupted electrocardiogram signals.

This paper proposes a novel machine learning-enabled framework to robustly monitor the instantaneous...

Correlation of compliance to statin therapy with lipid profile and serum HMGCoA reductase levels in dyslipidemic patients.

BACKGROUND: The efficacy of statin therapy may be lost or vary with reduction in compliance and inte...

Reduction of false arrhythmia alarms using signal selection and machine learning.

In this paper, we propose an algorithm that classifies whether a generated cardiac arrhythmia alarm ...

Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators.

Early recognition of ventricular fibrillation (VF) and electrical therapy are key for the survival o...

Artificial Neural Network for Total Laboratory Automation to Improve the Management of Sample Dilution.

Diluting a sample to obtain a measure within the analytical range is a common task in clinical labor...

Compounding and stability evaluation of atorvastatin extemporaneous oral suspension using tablets or pure powder.

BACKGROUND: Statins are the first-line therapy for lowering high lipid levels. Atorvastatin calcium ...

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