A novel application of deep learning for single-lead ECG classification
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2018/08/01
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Indian UGC (journal)
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Refrences66
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Citations185
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Sherin M. Mathews
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Chandra Kambhamettu
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Kenneth E. Barner
Journal Categories
Medicine
Medicine (General)
Computer applications to medicine
Medical informatics
Medicine
Medicine (General)
Medical technology
Science
Biology (General)
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
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Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Real-Time Continuous Pose Recovery of Human Hands Using Convolutional Networks | ACM Transactions on Graphics |
| 238 | 2014 |
| Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups | 2012 | |||
| Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition | 2012 | |||
| Block-based neural networks for personalized ECG signal classification | 2007 | |||
A Fast Learning Algorithm for Deep Belief Nets | Neural Computation |
| 6,903 | 2006 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Improving deep-learning electrocardiogram classification with an effective coloring method | Artificial Intelligence in Medicine |
| 2024 | |
| An intelligent deep neural network with Opposition based Laplacian Equilibrium Optimizer to improve feature extraction using ECG signals | Biomedical Signal Processing and Control |
| 2024 | |
| CAT-Net: Convolution, attention, and transformer based network for single-lead ECG arrhythmia classification | Biomedical Signal Processing and Control |
| 2024 | |
| Cardiovascular hardware simulator and artificial aorta-generated central blood pressure waveform database according to various vascular ages for cardiovascular health monitoring applications | Computers in Biology and Medicine |
| 2024 | |
Classification feasibility test on multi-lead electrocardiography signals generated from single-lead electrocardiography signals | Scientific Reports |
| 2024 |
Citations Analysis
The category
Medicine: Medicine (General): Medical technology 63
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Dense Convolutional Networks With Focal Loss and Image Generation for Electrocardiogram Classification and was published in 2019. The most recent citation comes from a 2024 study titled An Automated Cardiac Arrhythmia Classification Network for 45 Arrhythmia Classes Using 12-Lead Electrocardiogram. This article reached its peak citation in 2022, with 50 citations. It has been cited in 90 different journals, 21% of which are open access. Among related journals, the IEEE Access cited this research the most, with 23 citations. The chart below illustrates the annual citation trends for this article.