AIMC Topic: Arrhythmias, Cardiac

Clear Filters Showing 51 to 60 of 280 articles

Applying Artificial Intelligence for Phenotyping of Inherited Arrhythmia Syndromes.

The Canadian journal of cardiology Apr 24, 2024
Inherited arrhythmia disorders account for a significant proportion of sudden cardiac death, particularly among young individuals. Recent advances in our understanding of these syndromes have improved patient diagnosis and care, yet certain clinical ...
Machine Learning Humans Phenotype Artificial Intelligence Genetic Testing Arrhythmias, Cardiac Death, Sudden, Cardiac
View on PubMed DOI

Classification Method of ECG Signals Based on RANet.

Cardiovascular engineering and technology Apr 23, 2024
BACKGROUND: Electrocardiograms (ECG) are an important source of information on human heart health and are widely used to detect different types of arrhythmias.
Reproducibility of Results Diagnosis, Computer-Assisted Deep Learning Neural Networks, Computer Databases, Factual Signal Processing, Computer-Assisted Arrhythmias, Cardiac Heart Rate Electrocardiography Action Potentials Humans Predictive Value of Tests
View on PubMed DOI

Cardiac Arrhythmia Classification Using Advanced Deep Learning Techniques on Digitized ECG Datasets.

Sensors (Basel, Switzerland) Apr 12, 2024
ECG classification or heartbeat classification is an extremely valuable tool in cardiology. Deep learning-based techniques for the analysis of ECG signals assist human experts in the timely diagnosis of cardiac diseases and help save precious lives. ...
Algorithms Deep Learning Electrocardiography Humans Neural Networks, Computer Heart Rate Signal Processing, Computer-Assisted Arrhythmias, Cardiac
View on PubMed DOI

Impact of artificial intelligence arrhythmia mapping on time to first ablation, procedure duration, and fluoroscopy use.

Journal of cardiovascular electrophysiology Mar 4, 2024
INTRODUCTION: Artificial intelligence (AI) ECG arrhythmia mapping provides arrhythmia source localization using 12-lead ECG data; whether this information impacts procedural efficiency is unknown. We performed a retrospective, case-control study to e...
Heart Rate Catheter Ablation Time-to-Treatment Fluoroscopy Arrhythmias, Cardiac Electrophysiologic Techniques, Cardiac Time Factors Electrocardiography Treatment Outcome Action Potentials Operative Time Predictive Value of Tests Male Middle Aged Case-Control Studies Female Aged Humans Artificial Intelligence Retrospective Studies
View on PubMed DOI

Monitoring of Remotely Reprogrammable Implantable Loop Recorders With Algorithms to Reduce False-Positive Alerts.

Journal of the American Heart Association Feb 23, 2024
BACKGROUND: Implantable loop recorders (ILRs) are increasingly placed for arrhythmia detection. However, historically, ≈75% of ILR alerts are false positives, requiring significant time and effort for adjudication. The LINQII and LUX-Dx are remotely ...
Electrocardiography, Ambulatory Arrhythmias, Cardiac Early Diagnosis Artificial Intelligence Humans Algorithms Prostheses and Implants
View on PubMed DOI

Person identification with arrhythmic ECG signals using deep convolution neural network.

Scientific reports Feb 23, 2024
Over the past decade, the use of biometrics in security systems and other applications has grown in popularity. ECG signals in particular are attracting increased attention due to their characteristics, which are required for a trustworthy identifica...
Humans Signal Processing, Computer-Assisted Arrhythmias, Cardiac Heart Rate Neural Networks, Computer Biometry Algorithms Electrocardiography
View on PubMed DOI

Towards Flexible and Low-Power Wireless Smart Sensors: Reconfigurable Analog-to-Feature Conversion for Healthcare Applications.

Sensors (Basel, Switzerland) Feb 3, 2024
Analog-to-feature (A2F) conversion based on non-uniform wavelet sampling (NUWS) has demonstrated the ability to reduce energy consumption in wireless sensors while employed for electrocardiogram (ECG) anomaly detection. The technique involves extract...
Humans Neural Networks, Computer Electrocardiography Arrhythmias, Cardiac
View on PubMed DOI

Scalar invariant transform based deep learning framework for detecting heart failures using ECG signals.

Scientific reports Feb 1, 2024
Heart diseases are leading to death across the globe. Exact detection and treatment for heart disease in its early stages could potentially save lives. Electrocardiogram (ECG) is one of the tests that take measures of heartbeat fluctuations. The devi...
Signal Processing, Computer-Assisted Heart Failure Arrhythmias, Cardiac Algorithms Deep Learning Electrocardiography Humans
View on PubMed DOI

CLINet: A novel deep learning network for ECG signal classification.

Journal of electrocardiology Jan 28, 2024
Machine learning is poised to revolutionize medicine with algorithms that spot cardiac arrhythmia. An automated diagnostic approach can boost the efficacy of diagnosing life-threatening arrhythmia disorders in routine medical procedures. In this pape...
Signal Processing, Computer-Assisted Arrhythmias, Cardiac Humans Algorithms Software Deep Learning Electrocardiography
View on PubMed DOI

Heart failure classification using deep learning to extract spatiotemporal features from ECG.

BMC medical informatics and decision making Jan 15, 2024
BACKGROUND: Heart failure is a syndrome with complex clinical manifestations. Due to increasing population aging, heart failure has become a major medical problem worldwide. In this study, we used the MIMIC-III public database to extract the temporal...
Heart Failure Arrhythmias, Cardiac Deep Learning Electrocardiography Humans Algorithms Databases, Factual
View on PubMed DOI
Popular Topics
Recent Journals