Latest AI and machine learning research in myocardial infarction for healthcare professionals.
BACKGROUND: About 40% of clopidogrel-treated patients display high platelet reactivity (HPR). Altern...
Identification of alarming features in the electrocardiogram (ECG) signal is extremely significant f...
To lessen the rate of false critical arrhythmia alarms, we used robust heart rate estimation and cos...
In this study, we developed a sandwich aptamer-based screen-printed carbon electrode (SPCE) using ch...
BACKGROUND: Reports of left-sided brain malignancies among interventional cardiologists have heighte...
BACKGROUND: The following registry (Katowice-Zabrze retrospective registry) aimed to assess the infl...
INTRODUCTION: There is a multitude of evidence supporting the benefit of statin use in cardiovascula...
In the present study, it has been shown that an unnecessary implantable cardioverter-defibrillator (...
INTRODUCTION AND OBJECTIVES: To assess the predictive value of atrial natriuretic peptide, β-type na...
Bronchial inflammation contributes to a sustained elevation of airway hyperresponsiveness (AHR) in a...
This paper proposes a novel machine learning-enabled framework to robustly monitor the instantaneous...
BACKGROUND: The efficacy of statin therapy may be lost or vary with reduction in compliance and inte...
In this paper, we propose an algorithm that classifies whether a generated cardiac arrhythmia alarm ...
Early recognition of ventricular fibrillation (VF) and electrical therapy are key for the survival o...
Diluting a sample to obtain a measure within the analytical range is a common task in clinical labor...
BACKGROUND: Statins are the first-line therapy for lowering high lipid levels. Atorvastatin calcium ...
The safety and feasibility of robotically-assisted percutaneous coronary intervention (PCI) for simp...
This paper addresses the challenge of extracting meaningful information from measured bioelectric si...
Long-term electrocardiogram (ECG) has become one of the important diagnostic assist methods in clini...
In this study, Random Forests (RF) classifier is proposed for ECG heartbeat signal classification in...
This study aims to determine the safety and efficacy of complete versus staged-percutaneous coronary...