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PUBMED FOR HANDHELDS

Journal Abstract Search


126 related items for PubMed ID: 38553158

  • 1. ECG-based cardiac arrhythmias detection through ensemble learning and fusion of deep spatial-temporal and long-range dependency features.
    Din S, Qaraqe M, Mourad O, Qaraqe K, Serpedin E.
    Artif Intell Med; 2024 Apr; 150():102818. PubMed ID: 38553158
    [Abstract] [Full Text] [Related]

  • 2. An Arrhythmia Classification Model Based on a CNN-LSTM-SE Algorithm.
    Sun A, Hong W, Li J, Mao J.
    Sensors (Basel); 2024 Sep 29; 24(19):. PubMed ID: 39409344
    [Abstract] [Full Text] [Related]

  • 3. A coordinated adaptive multiscale enhanced spatio-temporal fusion network for multi-lead electrocardiogram arrhythmia detection.
    Yang Z, Jin A, Li Y, Yu X, Xu X, Wang J, Li Q, Guo X, Liu Y.
    Sci Rep; 2024 Sep 06; 14(1):20828. PubMed ID: 39242748
    [Abstract] [Full Text] [Related]

  • 4. A hybrid deep learning network for automatic diagnosis of cardiac arrhythmia based on 12-lead ECG.
    Bai X, Dong X, Li Y, Liu R, Zhang H.
    Sci Rep; 2024 Oct 18; 14(1):24441. PubMed ID: 39424921
    [Abstract] [Full Text] [Related]

  • 5. Ensemble classifier fostered detection of arrhythmia using ECG data.
    Ramkumar M, Alagarsamy M, Balakumar A, Pradeep S.
    Med Biol Eng Comput; 2023 Sep 18; 61(9):2453-2466. PubMed ID: 37145258
    [Abstract] [Full Text] [Related]

  • 6. A Hybrid Deep Learning Approach for ECG-Based Arrhythmia Classification.
    Madan P, Singh V, Singh DP, Diwakar M, Pant B, Kishor A.
    Bioengineering (Basel); 2022 Apr 02; 9(4):. PubMed ID: 35447712
    [Abstract] [Full Text] [Related]

  • 7. The prediction of cardiac abnormality and enhancement in minority class accuracy from imbalanced ECG signals using modified deep neural network models.
    Rai HM, Chatterjee K, Dashkevych S.
    Comput Biol Med; 2022 Nov 02; 150():106142. PubMed ID: 36182760
    [Abstract] [Full Text] [Related]

  • 8. A Parallel Cross Convolutional Recurrent Neural Network for Automatic Imbalanced ECG Arrhythmia Detection with Continuous Wavelet Transform.
    Toma TI, Choi S.
    Sensors (Basel); 2022 Sep 28; 22(19):. PubMed ID: 36236496
    [Abstract] [Full Text] [Related]

  • 9. HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN.
    Islam MS, Hasan KF, Sultana S, Uddin S, Lio' P, Quinn JMW, Moni MA.
    Neural Netw; 2023 May 28; 162():271-287. PubMed ID: 36921434
    [Abstract] [Full Text] [Related]

  • 10. Constrained transformer network for ECG signal processing and arrhythmia classification.
    Che C, Zhang P, Zhu M, Qu Y, Jin B.
    BMC Med Inform Decis Mak; 2021 Jun 09; 21(1):184. PubMed ID: 34107920
    [Abstract] [Full Text] [Related]

  • 11. Classification of Electrocardiography Hybrid Convolutional Neural Network-Long Short Term Memory with Fully Connected Layer.
    Ramachandran D, Kumar RS, Alkhayyat A, Malik RQ, Srinivasan P, Priya GG, Gosu Adigo A.
    Comput Intell Neurosci; 2022 Jun 09; 2022():6348424. PubMed ID: 35860642
    [Abstract] [Full Text] [Related]

  • 12. A new approach for arrhythmia classification using deep coded features and LSTM networks.
    Yildirim O, Baloglu UB, Tan RS, Ciaccio EJ, Acharya UR.
    Comput Methods Programs Biomed; 2019 Jul 09; 176():121-133. PubMed ID: 31200900
    [Abstract] [Full Text] [Related]

  • 13. Cardiac Arrhythmia Classification Using Advanced Deep Learning Techniques on Digitized ECG Datasets.
    Sattar S, Mumtaz R, Qadir M, Mumtaz S, Khan MA, De Waele T, De Poorter E, Moerman I, Shahid A.
    Sensors (Basel); 2024 Apr 12; 24(8):. PubMed ID: 38676101
    [Abstract] [Full Text] [Related]

  • 14. Classification of Arrhythmia in Heartbeat Detection Using Deep Learning.
    Ullah W, Siddique I, Zulqarnain RM, Alam MM, Ahmad I, Raza UA.
    Comput Intell Neurosci; 2021 Apr 12; 2021():2195922. PubMed ID: 34712316
    [Abstract] [Full Text] [Related]

  • 15. Arrhythmia detection using deep convolutional neural network with long duration ECG signals.
    Yıldırım Ö, Pławiak P, Tan RS, Acharya UR.
    Comput Biol Med; 2018 Nov 01; 102():411-420. PubMed ID: 30245122
    [Abstract] [Full Text] [Related]

  • 16. [Deep residual convolutional neural network for recognition of electrocardiogram signal arrhythmias].
    Li D, Zhang H, Liu Z, Huang J, Wang T.
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2019 Apr 25; 36(2):189-198. PubMed ID: 31016934
    [Abstract] [Full Text] [Related]

  • 17. An Improved Convolutional Neural Network Based Approach for Automated Heartbeat Classification.
    Wang H, Shi H, Chen X, Zhao L, Huang Y, Liu C.
    J Med Syst; 2019 Dec 18; 44(2):35. PubMed ID: 31853698
    [Abstract] [Full Text] [Related]

  • 18. Automated diagnosis of arrhythmia using combination of CNN and LSTM techniques with variable length heart beats.
    Oh SL, Ng EYK, Tan RS, Acharya UR.
    Comput Biol Med; 2018 Nov 01; 102():278-287. PubMed ID: 29903630
    [Abstract] [Full Text] [Related]

  • 19. Automatic classification of arrhythmias using multi-branch convolutional neural networks based on channel-based attention and bidirectional LSTM.
    Liu F, Li H, Wu T, Lin H, Lin C, Han G.
    ISA Trans; 2023 Jul 01; 138():397-407. PubMed ID: 36898911
    [Abstract] [Full Text] [Related]

  • 20. ECG-based multi-class arrhythmia detection using spatio-temporal attention-based convolutional recurrent neural network.
    Zhang J, Liu A, Gao M, Chen X, Zhang X, Chen X.
    Artif Intell Med; 2020 Jun 01; 106():101856. PubMed ID: 32593390
    [Abstract] [Full Text] [Related]


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