A New 12-Lead ECG Signals Fusion Method Using Evolutionary CNN Trees for Arrhythmia Detection
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- @Article{meqdad:2022:Mathematics,
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author = "Maytham N. Meqdad and Fardin Abdali-Mohammadi and
Seifedine Kadry",
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title = "A New 12-Lead {ECG} Signals Fusion Method Using
Evolutionary {CNN} Trees for Arrhythmia Detection",
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journal = "Mathematics",
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year = "2022",
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volume = "10",
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number = "11",
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pages = "Article No. 1911",
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keywords = "genetic algorithms, genetic programming",
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ISSN = "2227-7390",
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URL = "https://www.mdpi.com/2227-7390/10/11/1911",
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DOI = "doi:10.3390/math10111911",
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abstract = "The 12 leads of electrocardiogram (ECG) signals show
the heart activities from different angles of coronal
and axial planes; hence, the signals of these 12 leads
have functional dependence on each other. This paper
proposes a novel method for fusing the data of 12-lead
ECG signals to diagnose heart problems. In the first
phase of the proposed method, the time-frequency
transform is employed to fuse the functional data of
leads and extract the frequency data of ECG signals in
12 leads. After that, their dependence is evaluated
through the correlation analysis. In the second phase,
a structural learning method is adopted to extract the
structural data from these 12 leads. Moreover, deep
convolutional neural network (CNN) models are coded in
this phase through genetic programming. These trees are
responsible for learning deep structural features from
functional data extracted from 12 leads. These trees
are upgraded through the execution of the genetic
programming (GP) algorithm to extract the optimal
features. These two phases are used together to fuse
the leads of ECG signals to diagnose various heart
problems. According to the test results on ChapmanECG,
including the signals of 10,646 patients, the proposed
method enjoys the mean accuracy of 97.60percent in the
diagnosis of various types of arrhythmias in the
Chapman dataset. It also outperformed the
state-of-the-art methods.",
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notes = "also known as \cite{math10111911}",
- }
Genetic Programming entries for
Maytham N Meqdad
Fardin Abdali-Mohammadi
Seifedine Kadry
Citations