[HTML][HTML] Clinical applications of artificial intelligence and machine learning in the modern cardiac intensive care unit

JC Jentzer, AH Kashou, DH Murphree - Intelligence-Based Medicine, 2023‏ - Elsevier
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 …

Application of artificial intelligence in the diagnosis and treatment of cardiac arrhythmia

RX Guo, X Tian, G Bazoukis, G Tse… - Pacing and Clinical …, 2024‏ - Wiley Online Library
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 …

Improving deep-learning electrocardiogram classification with an effective coloring method

WW Chen, CC Tseng, CC Huang, HHS Lu - Artificial intelligence in …, 2024‏ - Elsevier
Cardiovascular diseases, particularly arrhythmias, remain a leading cause of mortality
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

R Doste, M Lozano, G Jimenez-Perez, L Mont… - Frontiers in …, 2022‏ - frontiersin.org
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 …

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 …

[HTML][HTML] Pharmacotherapy in ventricular arrhythmias

N Apte, DK Kalra - Cardiology, 2023‏ - karger.com
Background: Ventricular ectopy is observed in most of the population ranging from isolated
premature ventricular contractions to rapid hemodynamically unstable ventricular …

Assessing the reidentification risks posed by deep learning algorithms applied to ECG data

A Ghazarian, J Zheng, D Struppa, C Rakovski - IEEE Access, 2022‏ - ieeexplore.ieee.org
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 …

[HTML][HTML] Electrocardiographic Characteristics, identification, and management of frequent premature ventricular contractions

D Tsiachris, M Botis, I Doundoulakis, LI Bartsioka… - Diagnostics, 2023‏ - mdpi.com
Premature ventricular complexes (PVCs) are frequently encountered in clinical practice. The
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

TY Chang, KW Chen, CM Liu, SL Chang… - Journal of Personalized …, 2022‏ - mdpi.com
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 …

[HTML][HTML] Source Localization and Classification of Pulmonary Valve-Originated Electrocardiograms Using Volume Conductor Modeling with Anatomical Models

K Ogawa, A Hirata - Biosensors, 2024‏ - pmc.ncbi.nlm.nih.gov
Premature ventricular contractions (PVCs) are a common arrhythmia characterized by
ectopic excitations within the ventricles. Accurately estimating the ablation site using an …