AIMC Topic: Arrhythmias, Cardiac

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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...
Electrocardiography Arrhythmias, Cardiac Humans Neural Networks, Computer
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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...
Humans Algorithms Signal Processing, Computer-Assisted Heart Failure Arrhythmias, Cardiac Deep Learning Electrocardiography
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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...
Humans Software Electrocardiography Signal Processing, Computer-Assisted Arrhythmias, Cardiac Algorithms Deep Learning
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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...
Electrocardiography Heart Failure Arrhythmias, Cardiac Databases, Factual Deep Learning Humans Algorithms
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ECG arrhythmia detection in an inter-patient setting using Fourier decomposition and machine learning.

Medical engineering & physics Jan 9, 2024
ECG beat classification or arrhythmia detection through artificial intelligence (AI) is an active topic of research. It is vital to recognize and detect the type of arrhythmia for monitoring cardiac abnormalities. The AI-based ECG beat classification...
Arrhythmias, Cardiac Heart Rate Algorithms Electrocardiography Support Vector Machine Signal Processing, Computer-Assisted Humans Artificial Intelligence
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Novel application of convolutional neural networks for artificial intelligence-enabled modified moving average analysis of P-, R-, and T-wave alternans for detection of risk for atrial and ventricular arrhythmias.

Journal of electrocardiology Dec 26, 2023
BACKGROUND: T-wave alternans (TWA) analysis was shown in >14,000 individuals studied worldwide over the past two decades to be a useful tool to assess risk for cardiovascular mortality and sudden arrhythmic death. TWA analysis by the modified moving ...
Arrhythmias, Cardiac Heart Atria Neural Networks, Computer Artificial Intelligence Electrocardiography Humans Electrocardiography, Ambulatory Reproducibility of Results
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ECG-Based Multiclass Arrhythmia Classification Using Beat-Level Fusion Network.

Journal of healthcare engineering Nov 29, 2023
Cardiovascular disease (CVD) is one of the most severe diseases threatening human life. Electrocardiogram (ECG) is an effective way to detect CVD. In recent years, many methods have been proposed to detect arrhythmia using 12-lead ECG. In particular,...
Signal Processing, Computer-Assisted Algorithms Humans Arrhythmias, Cardiac Electrocardiography Neural Networks, Computer
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Artificial Intelligence ECG Analysis in Patients with Short QT Syndrome to Predict Life-Threatening Arrhythmic Events.

Sensors (Basel, Switzerland) Nov 1, 2023
Short QT syndrome (SQTS) is an inherited cardiac ion-channel disease related to an increased risk of sudden cardiac death (SCD) in young and otherwise healthy individuals. SCD is often the first clinical presentation in patients with SQTS. However, a...
Humans Neural Networks, Computer Death, Sudden, Cardiac Artificial Intelligence Electrocardiography Arrhythmias, Cardiac
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Cardiac arrhythmia detection using deep learning approach and time frequency representation of ECG signals.

BMC medical informatics and decision making Oct 19, 2023
BACKGROUND: Cardiac arrhythmia is a cardiovascular disorder characterized by disturbances in the heartbeat caused by electrical conduction anomalies in cardiac muscle. Clinically, ECG machines are utilized to diagnose and monitor cardiac arrhythmia n...
Electrocardiography Signal Processing, Computer-Assisted Cardiovascular Diseases Deep Learning Humans Arrhythmias, Cardiac Algorithms
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Comparison of Machine Learning Algorithms Using Manual/Automated Features on 12-Lead Signal Electrocardiogram Classification: A Large Cohort Study on Students Aged Between 6 to 18 Years Old.

Cardiovascular engineering and technology Oct 17, 2023
PROPOSE: An electrocardiogram (ECG) has been extensively used to detect rhythm disturbances. We sought to determine the accuracy of different machine learning in distinguishing abnormal ECGs from normal ones in children who were examined using a rest...
Machine Learning Arrhythmias, Cardiac Child Algorithms Electrocardiography Adolescent Adult Humans Cohort Studies
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