Unraveling Arrhythmias with Graph-Based Analysis: A Survey of the MIT-BIH Database
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2024/01/25
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Journal
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Indian UGC (journal)
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Refrences77
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Citations1
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Sadiq Alinsaif College of Computer Science and Engineering, University of Hafr Al Batin, Al Jamiah, Hafar Al Batin 39524, Saudi Arabia ORCID (unauthenticated)
Abstract
Cite
Alinsaif, Sadiq. “Unraveling Arrhythmias With Graph-Based Analysis: A Survey of the MIT-BIH Database”. Computation, vol. 12, no. 2, 2024, p. 21, https://doi.org/10.3390/computation12020021.
Alinsaif, S. (2024). Unraveling Arrhythmias with Graph-Based Analysis: A Survey of the MIT-BIH Database. Computation, 12(2), 21. https://doi.org/10.3390/computation12020021
Alinsaif, Sadiq. “Unraveling Arrhythmias With Graph-Based Analysis: A Survey of the MIT-BIH Database”. Computation 12, no. 2 (2024): 21. https://doi.org/10.3390/computation12020021.
Alinsaif S. Unraveling Arrhythmias with Graph-Based Analysis: A Survey of the MIT-BIH Database. Computation. 2024;12(2):21.
Journal Categories
Science
Mathematics
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| A novel unsupervised domain adaptation framework based on graph convolutional network and multi-level feature alignment for inter-subject ECG classification | Expert Systems with Applications |
| 9 | 2023 |
| Self-Attention LSTM-FCN model for arrhythmia classification and uncertainty assessment | Artificial Intelligence in Medicine |
| 8 | 2023 |
| BTAD: A binary transformer deep neural network model for anomaly detection in multivariate time series data | Advanced Engineering Informatics |
| 15 | 2023 |
A novel automated tower graph based ECG signal classification method with hexadecimal local adaptive binary pattern and deep learning | Journal of Ambient Intelligence and Humanized Computing |
| 29 | 2023 |
ECG-ViT: A Transformer-Based ECG Classifier for Energy-Constraint Wearable Devices | Journal of Sensors |
| 5 | 2022 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
COVID-19 Image Classification: A Comparative Performance Analysis of Hand-Crafted vs. Deep Features | Computation |
| 2024 |
Citations Analysis
| Category | Category Repetition |
|---|---|
| Science: Mathematics: Instruments and machines: Electronic computers. Computer science | 1 |
| Science: Mathematics | 1 |
The category
Science: Mathematics: Instruments and machines: Electronic computers. Computer science 1
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled COVID-19 Image Classification: A Comparative Performance Analysis of Hand-Crafted vs. Deep Features and was published in 2024. The most recent citation comes from a 2024 study titled COVID-19 Image Classification: A Comparative Performance Analysis of Hand-Crafted vs. Deep Features. This article reached its peak citation in 2024, with 1 citations. It has been cited in 1 different journals, 100% of which are open access. Among related journals, the Computation cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.