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ECG autoencoder based on low-rank attention
The prevalence of cardiovascular disease (CVD) has surged in recent years, making it the foremost cause of mortality among humans. The...
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The influence of electrocardiogram (ECG) filters on the heights of R and T waves in children
Anesthesiologists often compare intraoperative and preoperative electrocardiogram (ECG) waveforms in patients undergoing general anesthesia. In...
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Feasibility of patch-type wireless 12-lead electrocardiogram in laypersons
Various efforts have been made to diagnose acute cardiovascular diseases (CVDs) early in patients. However, the sole option currently is symptom...
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IRIDIA-AF, a large paroxysmal atrial fibrillation long-term electrocardiogram monitoring database
Atrial fibrillation (AF) is the most common sustained heart arrhythmia in adults. Holter monitoring, a long-term 2-lead electrocardiogram (ECG), is a...
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Machine learning approaches that use clinical, laboratory, and electrocardiogram data enhance the prediction of obstructive coronary artery disease
Pretest probability (PTP) for assessing obstructive coronary artery disease (ObCAD) was updated to reduce overestimation. However, standard...
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Multichannel high noise level ECG denoising based on adversarial deep learning
This paper proposes a denoising method based on an adversarial deep learning approach for the post-processing of multi-channel fetal...
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Beat-wise segmentation of electrocardiogram using adaptive windowing and deep neural network
Timely detection of anomalies and automatic interpretation of an electrocardiogram (ECG) play a crucial role in many healthcare applications, such as...
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Congenital heart disease detection by pediatric electrocardiogram based deep learning integrated with human concepts
Early detection is critical to achieving improved treatment outcomes for child patients with congenital heart diseases (CHDs). Therefore, develo**...
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A large-scale multi-label 12-lead electrocardiogram database with standardized diagnostic statements
Deep learning approaches have exhibited a great ability on automatic interpretation of the electrocardiogram (ECG). However, large-scale public...
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Robust electrocardiogram delineation model for automatic morphological abnormality interpretation
Knowledge of electrocardiogram (ECG) wave signals is one of the essential steps in diagnosing heart abnormalities. Considerable performance with...
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Deep learning augmented ECG analysis to identify biomarker-defined myocardial injury
Chest pain is a common clinical complaint for which myocardial injury is the primary concern and is associated with significant morbidity and...
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Development of wearable multi-lead ECG measurement device using cubic flocked electrode
This paper describes the fabrication and fundamental evaluation of the cubic flocked electrode (CFE), which is a dry electrode that is fabricated...
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Association of major and minor ECG abnormalities with traditional cardiovascular risk factors in the general population: a large scale study
Cardiovascular disease (CVD) can be determined and quantified using the electrocardiogram (ECG) analysis. Identification of the risk factors...
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Securing Internet-of-Medical-Things networks using cancellable ECG recognition
Reinforcement of the Internet of Medical Things (IoMT) network security has become extremely significant as these networks enable both patients and...
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Multimodal ECG heartbeat classification method based on a convolutional neural network embedded with FCA
Arrhythmias are irregular heartbeat rhythms caused by various conditions. Automated ECG signal classification aids in diagnosing and predicting...
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Externally validated deep learning model to identify prodromal Parkinson’s disease from electrocardiogram
Little is known about electrocardiogram (ECG) markers of Parkinson’s disease (PD) during the prodromal stage. The aim of the study was to build a...
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Secure hardware IP of GLRT cascade using color interval graph based embedded fingerprint for ECG detector
This paper presents a security aware design methodology to design secure generalized likelihood ratio test (GLRT) hardware intellectual property (IP)...
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Certain investigation on hybrid neural network method for classification of ECG signal with the suitable a FIR filter
The Electrocardiogram (ECG) records are crucial for predicting heart diseases and evaluating patient’s health conditions. ECG signals provide...
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An old diagnostic tool for new indications: inpatient Holter ECG for conditions other than syncope or stroke
Holter electrocardiography (ECG) assists in the diagnosis of arrhythmias. Its use in the inpatient setting has been described solely for the...
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Scalar invariant transform based deep learning framework for detecting heart failures using ECG signals
Heart diseases are leading to death across the globe. Exact detection and treatment for heart disease in its early stages could potentially save...
