Papers ECG Classification
“ECG Classification” 태그가 달린 논문 153편 · 필터 해제
ECG Classification System for Arrhythmia Detection Using Convolutional Neural Networks
Arrhythmia is just one of the many cardiovascular illnesses that have been extensively studied throughout the years. Using multi-lead ECG data, this research describes a deep learning (DL) pipeline technique based on con…
Arrhythmia DetectionECG ClassificationMVKT-ECG: Efficient Single-lead ECG Classification on Multi-Label Arrhythmia by Multi-View Knowledge Transferring
The widespread emergence of smart devices for ECG has sparked demand for intelligent single-lead ECG-based diagnostic systems. However, it is challenging to develop a single-lead-based ECG interpretation model for multip…
DiagnosticECG ClassificationKnowledge DistillationProof of Swarm Based Ensemble Learning for Federated Learning Applications
Ensemble learning combines results from multiple machine learning models in order to provide a better and optimised predictive model with reduced bias, variance and improved predictions. However, in federated learning it…
ECG ClassificationEnsemble LearningFederated LearningA Dual-scale Lead-seperated Transformer With Lead-orthogonal Attention And Meta-information For Ecg Classification
Auxiliary diagnosis of cardiac electrophysiological status can be obtained through the analysis of 12-lead electrocardiograms (ECGs). This work proposes a dual-scale lead-separated transformer with lead-orthogonal attent…
ECG ClassificationAdvancing the State-of-the-Art for ECG Analysis through Structured State Space Models
The field of deep-learning-based ECG analysis has been largely dominated by convolutional architectures. This work explores the prospects of applying the recently introduced structured state space models (SSMs) as a part…
ECG ClassificationState Space ModelsTime SeriesTime Series AnalysisAnalysis of a Deep Learning Model for 12-Lead ECG Classification Reveals Learned Features Similar to Diagnostic Criteria
Despite their remarkable performance, deep neural networks remain unadopted in clinical practice, which is considered to be partially due to their lack in explainability. In this work, we apply attribution methods to a p…
ClassificationDiagnosticECG ClassificationSEVGGNet-LSTM: a fused deep learning model for ECG classification
This paper presents a fused deep learning algorithm for ECG classification. It takes advantages of the combined convolutional and recurrent neural network for ECG classification, and the weight allocation capability of a…
ClassificationDeep LearningECG ClassificationLeveraging Statistical Shape Priors in GAN-based ECG Synthesis
Electrocardiogram (ECG) data collection during emergency situations is challenging, making ECG data generation an efficient solution for dealing with highly imbalanced ECG training datasets. In this paper, we propose a n…
ECG ClassificationMultimodality Multi-Lead ECG Arrhythmia Classification using Self-Supervised Learning
Electrocardiogram (ECG) signal is one of the most effective sources of information mainly employed for the diagnosis and prediction of cardiovascular diseases (CVDs) connected with the abnormalities in heart rhythm. Clea…
ECG ClassificationKnowledge DistillationRhythmSelf-Knowledge Distillation+3A Compact Online-Learning Spiking Neuromorphic Biosignal Processor
Real-time biosignal processing on wearable devices has attracted worldwide attention for its potential in healthcare applications. However, the requirement of low-area, low-power and high adaptability to different patien…
ECG ClassificationDeep Learning-based ECG Classification on Raspberry PI using a Tensorflow Lite Model based on PTB-XL Dataset
The number of IoT devices in healthcare is expected to rise sharply due to increased demand since the COVID-19 pandemic. Deep learning and IoT devices are being employed to monitor body vitals and automate anomaly detect…
Anomaly DetectionECG ClassificationA Domain Generalization Approach for Out-Of-Distribution 12-lead ECG Classification with Convolutional Neural Networks
Deep Learning systems have achieved great success in the past few years, even surpassing human intelligence in several cases. As of late, they have also established themselves in the biomedical and healthcare domains, wh…
Domain GeneralizationECG ClassificationEnhancing Deep Learning-based 3-lead ECG Classification with Heartbeat Counting and Demographic Data Integration
Nowadays, an increasing number of people are being diagnosed with cardiovascular diseases (CVDs), the leading cause of death globally. The gold standard for identifying these heart problems is via electrocardiogram (ECG)…
ECG ClassificationLightX3ECG: A Lightweight and eXplainable Deep Learning System for 3-lead Electrocardiogram Classification
Cardiovascular diseases (CVDs) are a group of heart and blood vessel disorders that is one of the most serious dangers to human health, and the number of such patients is still growing. Early and accurate detection plays…
ECG ClassificationDecorrelative Network Architecture for Robust Electrocardiogram Classification
Artificial intelligence has made great progress in medical data analysis, but the lack of robustness and trustworthiness has kept these methods from being widely deployed. As it is not possible to train networks that are…
Adversarial AttackAdversarial DefenseClassificationECG ClassificationUsing Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications
Adversarial attacks such as poisoning attacks have attracted the attention of many machine learning researchers. Traditionally, poisoning attacks attempt to inject adversarial training data in order to manipulate the tra…
Activity RecognitionAnomaly DetectionData PoisoningECG Classification+3A Personalized Zero-Shot ECG Arrhythmia Monitoring System: From Sparse Representation Based Domain Adaption to Energy Efficient Abnormal Beat Detection for Practical ECG Surveillance
This paper proposes a low-cost and highly accurate ECG-monitoring system intended for personalized early arrhythmia detection for wearable mobile sensors. Earlier supervised approaches for personalized ECG monitoring req…
Arrhythmia DetectionDictionary LearningDomain AdaptationECG Classification+2Identifying Electrocardiogram Abnormalities Using a Handcrafted-Rule-Enhanced Neural Network
A large number of people suffer from life-threatening cardiac abnormalities, and electrocardiogram (ECG) analysis is beneficial to determining whether an individual is at risk of such abnormalities. Automatic ECG classif…
Clinical KnowledgeDeep LearningECG ClassificationClassification of ECG based on Hybrid Features using CNNs for Wearable Applications
Sudden cardiac death and arrhythmia account for a large percentage of all deaths worldwide. Electrocardiography (ECG) is the most widely used screening tool for cardiovascular diseases. Traditionally, ECG signals are cla…
Arrhythmia DetectionECG ClassificationElectrocardiography (ECG)Identifying Arrhythmias Based on ECG Classification Using Enhanced-PCA and Enhanced-SVM Methods
The "Cardio Vascular Diseases (CVDs)" had already attained worrisome proportions in both advanced and emerging nations in recent times. Physically inactive behaviors, altered eating, and occupational routines, and redu…
DenoisingECG ClassificationRhythm