ECG Interpretation with Deep LearningElectrocardiography (ECG), which can trace the electrical activity of the heart noninvasively, is widely used to assess heart health. Accurate interpretation of ECG requires significant amounts of...doi:10.1007/978-981-15-3824-7_8Wenjie Cai...
In particular, deep learning (DL) models find useful to increase the disease diagnostic performance of CVD using the ECG signals. To explore and achieve effective ECG recognition, this paper presents a Class Imbalance handing with DL based Gated Recurrent Unit (GRU) and Extreme Learning Machine (...
deep learningBackground: Electrocardiography (ECG) is a fundamental diagnostic tool, frequently used in clinical practice, for testing heart conditions. Recently, computer-adoi:10.2139/ssrn.3514790Zhu, HonglingCheng, ChengYin, HangLi, XingyiZuo, Ping...
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Electrocardiogram (ECG) serves as the gold standard for noninvasive diagnosis of several types of heart disorders. In this study, a novel hybrid approach o
Deep LearningElectrocardiogramIdentificationKerasMultinomial ClassificationNeupyElectrocardiogram (ECG) signal depicts electrical activity of the heart. It is primary used to obtain insight of heart abnormalities. Recently, it is found to be unique thus recommended to be used as a biometric modality like ...
This paper proposes a kernel size calculation based on P, Q, R, and S waves of one heartbeat to enhance classification accuracy in a deep learning framework. In addition, Electrocardiogram (ECG) signals were filtered using wavelet transform with dmey wavelet, in which the shape of the dmey ...
Cloud-based ECG Interpretation of Atrial Fibrillation Condition with Deep Learning TechniqueThe prevalent type of arrhythmia associated with an increased risk of stroke and mortality is atrial fibrillation (AF). It is a known priority to identify AF before the first complication occurs. No previous ...
Cleaning ECG with Deep Learning: A Denoiser Tested in Industrial SettingsGRUDenoiserECGIndustrythe popularity of wearables continues to scale, a substantial portion of the population has now access to (self-)monitorization of cardiovascular activity. In particular, the use of ECG ......
Deep learningFeature extractionBaseline wanderMuscle artifactPower line interferenceClassification of ECG noise (unwanted disturbance) plays a crucial role in the development of automated analysis systems for accurate diagnosis and detection of cardiac abnormalities. This paper mainly deals with the feature ...