Ensemble deep learning approach for ecg-based cardiac disease detection: Signal and image analysis
T Mahmud, A Barua, D Islam… - … on Information and …, 2023 - ieeexplore.ieee.org
The classification and identification of arrhythmias using ECG signals hold substantial
practical importance in the early prevention and detection of cardiac/cardiovascular …
practical importance in the early prevention and detection of cardiac/cardiovascular …
Deep representation learning with sample generation and augmented attention module for imbalanced ECG classification
Developing an efficient heartbeat monitoring system has become a focal point in numerous
healthcare applications. Specifically, in the last few years, heartbeat classification for …
healthcare applications. Specifically, in the last few years, heartbeat classification for …
Arrhythmia detection using TQWT, CEEMD and deep CNN-LSTM neural networks with ECG signals
Cardiac arrhythmia is a typically clinical manifestation of cardiovascular disease which leads
to serious health problem. Detection of arrhythmia is traditionally relying on manual …
to serious health problem. Detection of arrhythmia is traditionally relying on manual …
[HTML][HTML] A nonlinear analysis of cardiovascular diseases using multi-scale analysis and generalized hurst exponent
S Lahmiri - Healthcare Analytics, 2023 - Elsevier
Congestive heart failure (CHF) and arrhythmia (ARR) are common heart diseases that affect
a growing population of patients worldwide. In this work, we employ multi-scale analysis …
a growing population of patients worldwide. In this work, we employ multi-scale analysis …
Myocardial infarction detection using ITD, DWT and deterministic learning based on ECG signals
Nowadays, cardiovascular diseases (CVD) is one of the prime causes of human mortality,
which has received tremendous and elaborative research interests regarding the prevention …
which has received tremendous and elaborative research interests regarding the prevention …
A novel technique for the detection of myocardial dysfunction using ECG signals based on CEEMD, DWT, PSR and neural networks
The cardiovascular disease is one of the most serious health problems around the world.
Traditionally, detection of cardiac arrhythmia based on the visual inspection of …
Traditionally, detection of cardiac arrhythmia based on the visual inspection of …
Self-supervised learning for arrhythmia classification.
GAL Silva - 2023 - repositorio.ufop.br
Arrhythmias, heart diseases that are commonly diagnosed through electrocar-diograms
(ECG), require computational methods for detection and classification to improve the …
(ECG), require computational methods for detection and classification to improve the …
[PDF][PDF] Arrhythmia Prediction on Optimal Features Obtained from the ECG as Images.
FAM Al-Yarimi - Computer Systems Science & Engineering, 2023 - researchgate.net
A critical component of dealing with heart disease is real-time identification, which triggers
rapid action. The main challenge of real-time identification is illustrated here by the rare …
rapid action. The main challenge of real-time identification is illustrated here by the rare …
基于多重分形及其关联特征组合的心电信号分类.
卢清， 李秋生， 叶莉华， 许德鹏 - Application Research of …, 2023 - search.ebscohost.com
多重分形理论只是对分形体几何支集上任意一点观察到的奇异指数作统计分析.
多重分形关联研究的是具有不同奇异指数的两点之间的空间关联特性, 是对多重分形单点统计的 …
多重分形关联研究的是具有不同奇异指数的两点之间的空间关联特性, 是对多重分形单点统计的 …
Amazing Power of DINOv2 for Automatic Diagnosis of 12-Lead ECG
The Electrocardiogram (ECG) is a reliable and fast diagnostic test for detecting several heart
anomalies to enable timely intervention. However, accurate interpretation is crucial and …
anomalies to enable timely intervention. However, accurate interpretation is crucial and …