Giraffe: A Genetic Programming Algorithm To Build Deep Learning Ensembles For ECG Arrhythmia Classification
Created by W.Langdon from
gp-bibliography.bib Revision:1.8344
- @InProceedings{Kucharski:2024:ICIP,
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author = "Damian Kucharski and Agata M. Wijata and Lu Fu and
Weidong Lin and Yumei Xue and Jacek Kawa and
Yalin Zheng and Y. H. Gregory Lip and Jakub Nalepa",
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title = "Giraffe: A Genetic Programming Algorithm To Build Deep
Learning Ensembles For {ECG} Arrhythmia
Classification",
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booktitle = "2024 IEEE International Conference on Image Processing
(ICIP)",
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year = "2024",
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pages = "3070--3076",
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month = oct,
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keywords = "genetic algorithms, genetic programming, Deep
learning, ANN, Training, Analytical models, Arrhythmia,
Manuals, Electrocardiography, Ensemble Learning, ECG
Arrhythmia Classification, CVD",
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ISSN = "2381-8549",
-
DOI = "
doi:10.1109/ICIP51287.2024.10647780",
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abstract = "Cardiovascular diseases remain one of the leading
causes of death worldwide. Therefore, developing and
validating automated tools to help identify high-risk
patients are of paramount clinical utility. In this
article, we tackle this task and introduce a genetic
programming algorithm (called GIRAFFE) to build (deep)
machine learning classification ensembles for
arrhythmia classification from two-dimensional images
of 12-lead electrocardiogram (ECG) tracings. GIRAFFE
evolves the architecture, content, and fusion scheme of
the ensemble, to obtain an accurate yet lightweight
classification system. The experimental study performed
over a large-scale dataset of ECG images revealed that
our approach outperforms other ensemble methods and
carefully fine-tuned deep models, elaborates compact
heterogeneous ensembles, and does not require any user
intervention hence it is easy to apply to other
classification tasks.",
-
notes = "Also known as \cite{10647780}",
- }
Genetic Programming entries for
Damian Kucharski
Agata M Wijata
Lu Fu
Weidong Lin
Yumei Xue
Jacek Kawa
Yalin Zheng
Gregory Lip
Jakub Nalepa
Citations