Myocardial Infarction

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 ectopic heartbeat, can lead to life-threatening cardiac conditions. Computer-aided PVC detection is of considerable importance in medical centers or outpatient ECG rooms. In this paper, we proposed a new approach that combined deep neural networks and rules inference for PVC detection. The detection per...

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 data. For personalized radiation oncology, datasets representing the variation in the entire cancer patient population need to be acquired and used to learn prediction models. Ethical and legal boundaries to ensure data privacy hamper collaboration between research institutes. We hypothesize that d...

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 dyspnea by compressing healthy lung parenchyma and ...

Patient-Specific Deep Architectural Model for ECG Classification.

Heartbeat classification is a crucial step for arrhythmia diagnosis during electrocardiographic (ECG) analysis. The new scenario of wireless body sens...

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). Alternative treatments of HPR patients, identified by pl...

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 for the prediction of congestive heart failure (CHF...

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 cost-sensitive support vector machines. The PhysioNet...

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 chronoamperometry for the detection of cardiac tropo...

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 heightened concerns regarding physician radiation exposur...

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 influence of a chronic kidney disease (CKD) on long-te...

Impact of vitamin D status on statin-induced myopathy.

INTRODUCTION: There is a multitude of evidence supporting the benefit of statin use in cardiovascular disease; however, statin-induced myopathy is a m...

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 (ICD) shock is often delivered to patients with an ...

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 natriuretic peptide, copeptin, mid-regional pro-adre...

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 asthma. Conversely, omega-3 fatty acid derivatives ...

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 heart rate (IHR) from wrist-electrocardiography (...

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 intensity of statin therapy.

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 is true or false. The large number of false alarms...

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 of out-of-hospital cardiac arrest (OHCA) patients t...

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 laboratories. However, for urgent samples, it can cause...

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 (AtC) is the most commonly prescribed statin. It i...