AIMC Topic: Arrhythmias, Cardiac

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CS-based multi-task learning network for arrhythmia reconstruction and classification using ECG signals.

Physiological measurement Jul 5, 2023
. Although deep learning-based current methods have achieved impressive results in electrocardiograph (ECG) arrhythmia classification issues, they rely on using the original data to identify arrhythmia categories. However, a large amount of data gene...
Neural Networks, Computer Algorithms Humans Arrhythmias, Cardiac Pressure Electrocardiography Signal Processing, Computer-Assisted
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An end-end arrhythmia diagnosis model based on deep learning neural network with multi-scale feature extraction.

Physical and engineering sciences in medicine Jul 1, 2023
This study presents an innovative end-to-end deep learning arrhythmia diagnosis model that aims to address the problems in arrhythmia diagnosis. The model performs pre-processing of the heartbeat signal by automatically and efficiently extracting tim...
Heart Rate Humans Neural Networks, Computer Deep Learning Arrhythmias, Cardiac
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The use of digital health in heart rhythm care.

Expert review of cardiovascular therapy Jun 23, 2023
INTRODUCTION: Digital health is a broad term that includes telecommunication technologies to collect, share and manipulate health information to improve patient health and health care services. With the growing use of wearables, artificial intelligen...
Humans Artificial Intelligence Arrhythmias, Cardiac Machine Learning Medication Adherence
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A neuromorphic physiological signal processing system based on VO memristor for next-generation human-machine interface.

Nature communications Jun 21, 2023
Physiological signal processing plays a key role in next-generation human-machine interfaces as physiological signals provide rich cognition- and health-related information. However, the explosion of physiological signal data presents challenges for ...
Signal Processing, Computer-Assisted Arrhythmias, Cardiac Epilepsy Seizures Humans Neural Networks, Computer
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Leveling Up: A Review of Machine Learning Models in the Cardiac ICU.

The American journal of medicine Jun 19, 2023
Machine learning has emerged as a significant tool to augment the medical decision-making process. Studies have steadily accrued detailing algorithms and models designed using machine learning to predict and anticipate pathologic states. The cardiac ...
Intensive Care Units Arrhythmias, Cardiac Humans Artificial Intelligence Machine Learning Algorithms
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Transformer-based temporal sequence learners for arrhythmia classification.

Medical & biological engineering & computing Jun 6, 2023
An electrocardiogram (ECG) plays a crucial role in identifying and classifying cardiac arrhythmia. Traditional methods employ handcrafted features, and more recently, deep learning methods use convolution and recursive structures to classify heart si...
Humans Deep Learning Arrhythmias, Cardiac Electrocardiography Datasets as Topic
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NSICA: Multi-objective imperialist competitive algorithm for feature selection in arrhythmia diagnosis.

Computers in biology and medicine May 24, 2023
This study proposes a multi-objective, non-dominated, imperialist competitive algorithm (NSICA) to solve optimal feature selection problems. The NSICA is a multi-objective and discrete version of the original Imperialist Competitive Algorithm (ICA) t...
Arrhythmias, Cardiac Machine Learning Algorithms Humans
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Deep Learning Strategy for Sliding ECG Analysis during Cardiopulmonary Resuscitation: Influence of the Hands-Off Time on Accuracy.

Sensors (Basel, Switzerland) May 5, 2023
This study aims to present a novel deep learning algorithm for a sliding shock advisory decision during cardiopulmonary resuscitation (CPR) and its performance evaluation as a function of the cumulative hands-off time. We retrospectively used 13,570 ...
Humans Algorithms Retrospective Studies Ventricular Fibrillation Deep Learning Out-of-Hospital Cardiac Arrest Arrhythmias, Cardiac Electrocardiography Cardiopulmonary Resuscitation
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Flamingo-Optimization-Based Deep Convolutional Neural Network for IoT-Based Arrhythmia Classification.

Sensors (Basel, Switzerland) Apr 28, 2023
Cardiac arrhythmia is a deadly disease that threatens the lives of millions of people, which shows the need for earlier detection and classification. An abnormal signal in the heart causing arrhythmia can be detected at an earlier stage when the heal...
Heart Rate Birds Algorithms Signal Processing, Computer-Assisted Humans Electrocardiography Animals Arrhythmias, Cardiac Neural Networks, Computer
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Automated inter-patient arrhythmia classification with dual attention neural network.

Computer methods and programs in biomedicine Apr 20, 2023
BACKGROUND AND OBJECTIVES: Arrhythmia classification based on electrocardiograms (ECG) can enhance clinical diagnostic efficiency. However, due to the significant differences in the number of different categories of heartbeats, the performance of cla...
Heart Rate Neural Networks, Computer Algorithms Signal Processing, Computer-Assisted Humans Arrhythmias, Cardiac Databases, Factual Electrocardiography
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