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[HTML][HTML] Clinical applications of artificial intelligence and machine learning in the modern cardiac intensive care unit
The depth and breadth of data produced in the modern cardiac intensive care unit (CICU)
poses challenges to clinicians and researchers. Artificial intelligence (AI) and machine …
poses challenges to clinicians and researchers. Artificial intelligence (AI) and machine …
Application of artificial intelligence in the diagnosis and treatment of cardiac arrhythmia
The rapid growth in computational power, sensor technology, and wearable devices has
provided a solid foundation for all aspects of cardiac arrhythmia care. Artificial intelligence …
provided a solid foundation for all aspects of cardiac arrhythmia care. Artificial intelligence …
Improving deep-learning electrocardiogram classification with an effective coloring method
Cardiovascular diseases, particularly arrhythmias, remain a leading cause of mortality
worldwide. Electrocardiogram (ECG) analysis plays a pivotal role in cardiovascular disease …
worldwide. Electrocardiogram (ECG) analysis plays a pivotal role in cardiovascular disease …
Training machine learning models with synthetic data improves the prediction of ventricular origin in outflow tract ventricular arrhythmias
In order to determine the site of origin (SOO) in outflow tract ventricular arrhythmias (OTVAs)
before an ablation procedure, several algorithms based on manual identification of …
before an ablation procedure, several algorithms based on manual identification of …
Electrocardiogram Interpretation Using Artificial Intelligence: Diagnosis of Cardiac and Extracardiac Pathologic Conditions. How Far Has Machine Learning Reached?
G Raileanu, JSSG de Jong - Current Problems in Cardiology, 2024 - Elsevier
Artificial intelligence (AI) is already widely used in different fields of medicine, making
possible the integration of the paraclinical exams with the clinical findings in patients, for a …
possible the integration of the paraclinical exams with the clinical findings in patients, for a …
[HTML][HTML] Pharmacotherapy in ventricular arrhythmias
Background: Ventricular ectopy is observed in most of the population ranging from isolated
premature ventricular contractions to rapid hemodynamically unstable ventricular …
premature ventricular contractions to rapid hemodynamically unstable ventricular …
Assessing the reidentification risks posed by deep learning algorithms applied to ECG data
ECG (Electrocardiogram) data analysis is one of the most widely used and important tools in
cardiology diagnostics. In recent years the development of advanced deep learning …
cardiology diagnostics. In recent years the development of advanced deep learning …
[HTML][HTML] Electrocardiographic Characteristics, identification, and management of frequent premature ventricular contractions
Premature ventricular complexes (PVCs) are frequently encountered in clinical practice. The
association of PVCs with adverse cardiovascular outcomes is well established in the context …
association of PVCs with adverse cardiovascular outcomes is well established in the context …
[HTML][HTML] A high-precision deep learning algorithm to localize idiopathic ventricular arrhythmias
Background: An accurate prediction of ventricular arrhythmia (VA) origins can optimize the
strategy of ablation, and facilitate the procedure. Objective: This study aimed to develop a …
strategy of ablation, and facilitate the procedure. Objective: This study aimed to develop a …
[HTML][HTML] Source Localization and Classification of Pulmonary Valve-Originated Electrocardiograms Using Volume Conductor Modeling with Anatomical Models
Premature ventricular contractions (PVCs) are a common arrhythmia characterized by
ectopic excitations within the ventricles. Accurately estimating the ablation site using an …
ectopic excitations within the ventricles. Accurately estimating the ablation site using an …