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Liu, Chien-Liang; Xiao, Bin; Tsai, Cheng-Feng (2025) ECG-STAR: Spatio-temporal attention residual networks for multi-label ECG abnormality classification. Information Sciences, 717. doi:10.1016/j.ins.2025.122273

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Reference TypeJournal (article/letter/editorial)
TitleECG-STAR: Spatio-temporal attention residual networks for multi-label ECG abnormality classification
JournalInformation Sciences
AuthorsLiu, Chien-LiangAuthor
Xiao, BinAuthor
Tsai, Cheng-FengAuthor
Year2025 (November)Volume717
PublisherElsevier BV
DOIdoi:10.1016/j.ins.2025.122273Search in ResearchGate
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Mindat Ref. ID18441481Long-form Identifiermindat:1:5:18441481:9
GUID0
Full ReferenceLiu, Chien-Liang; Xiao, Bin; Tsai, Cheng-Feng (2025) ECG-STAR: Spatio-temporal attention residual networks for multi-label ECG abnormality classification. Information Sciences, 717. doi:10.1016/j.ins.2025.122273
Plain TextLiu, Chien-Liang; Xiao, Bin; Tsai, Cheng-Feng (2025) ECG-STAR: Spatio-temporal attention residual networks for multi-label ECG abnormality classification. Information Sciences, 717. doi:10.1016/j.ins.2025.122273
In(2025) Information Sciences Vol. 717. Elsevier BV

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Not Yet Imported: - journal-article : 10.1016/j.jacc.2020.11.010

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Al-Zaiti (2023) Nat. Med. Machine learning for ecg diagnosis and risk stratification of occlusion myocardial infarction , 1
He (2016) Deep residual learning for image recognition , 770
Not Yet Imported: - journal-article : 10.1162/neco.1997.9.8.1735

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Chen (2019) Large-scale classification of 12-lead ecg with deep learning , 1
Dosovitskiy ()
Vaswani (2017) Adv. Neural Inf. Process. Syst. Attention is all you need 30
Not Yet Imported: - journal-article : 10.1016/j.bspc.2018.03.003

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Not Yet Imported: - journal-article : 10.1109/TBME.2015.2468589

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Not Yet Imported: Pattern Recognition Letters - journal-article : 10.1016/j.patrec.2019.02.016

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Not Yet Imported: - journal-article : 10.1109/TSMC.2017.2705582

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Khan (2015) Ecg feature extraction in temporal domain and detection of various heart conditions , 1
Cho ()
Salloum (2017) Ecg-based biometrics using recurrent neural networks , 2062
Not Yet Imported: - journal-article : 10.1016/j.compbiomed.2018.03.016

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Not Yet Imported: Scientific Reports - journal-article : 10.1038/s41598-021-92172-5

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Natarajan (2020) A wide and deep transformer neural network for 12-lead ecg classification , 1
Sakli (2022) Comput. Intell. Neurosci. Resnet-50 for 12-lead electrocardiogram automated diagnosis , 2022
Not Yet Imported: - journal-article : 10.1155/2021/6649970

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Huang (2017) Densely connected convolutional networks , 4700
Ullah (2022) Comput. Intell. Neurosci. An end-to-end cardiac arrhythmia recognition method with an effective densenet model on imbalanced datasets using ecg signal , 2022
Not Yet Imported: - journal-article : 10.1016/j.compbiomed.2019.103378

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Hu (2018) Squeeze-and-excitation networks , 7132
Not Yet Imported: - journal-article : 10.1016/j.cmpb.2021.106521

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Wang (2020) Eca-net: efficient channel attention for deep convolutional neural networks , 11534
Ioffe (2015) Batch normalization: accelerating deep network training by reducing internal covariate shift , 448
Nair (2010) Rectified linear units improve restricted Boltzmann machines , 807
Not Yet Imported: IEEE Journal of Biomedical and Health Informatics - journal-article : 10.1109/JBHI.2020.3022989

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Not Yet Imported: Journal of Medical Imaging and Health Informatics - journal-article : 10.1166/jmihi.2018.2442

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Not Yet Imported: - journal-article : 10.1016/j.isci.2020.100886

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Alday (2020) Physiol. Meas. Classification of 12-lead ecgs: the physionet/computing in cardiology challenge 2020 41
Nonaka (2021) In-depth benchmarking of deep neural network architectures for ecg diagnosis , 414
Loshchilov ()
Not Yet Imported: - journal-article : 10.1016/j.inffus.2019.06.024

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Not Yet Imported: - journal-article : 10.1109/JBHI.2020.2981526

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Not Yet Imported: - journal-article : 10.1109/TSMC.2023.3257022

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Jyotishi (2020) An attention based hierarchical lstm model for detection of myocardial infarction , 1
Not Yet Imported: IEEE Transactions on Emerging Topics in Computational Intelligence - journal-article : 10.1109/TETCI.2023.3235374

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Liu (2025) Inf. Fusion Multimodal fusion of spatial-temporal and frequency representations for enhanced ecg classification
Not Yet Imported: - journal-article : 10.1016/j.knosys.2023.110545

If you would like this item imported into the Digital Library, please contact us quoting Journal ID
Not Yet Imported: - journal-article : 10.1016/j.knosys.2021.107508

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Ciocîrlan (2023) Techniques of biological signals classification and comparisons using machine learning techniques , 467


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