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Journal Abstract Search

415 related items for PubMed ID: 29111840

  • 21. Cardiac Severity Classification Using Pre Trained Neural Networks.
    Malleswari PN, Bindu CH, Prasad KS.
    Interdiscip Sci; 2021 Sep; 13(3):443-450. PubMed ID: 33481208
    [Abstract] [Full Text] [Related]

  • 22. Design of a Biorthogonal Wavelet Transform Based R-Peak Detection and Data Compression Scheme for Implantable Cardiac Pacemaker Systems.
    Kumar A, Kumar M, Komaragiri R.
    J Med Syst; 2018 Apr 19; 42(6):102. PubMed ID: 29675598
    [Abstract] [Full Text] [Related]

  • 23. Arrhythmia recognition and classification using combined linear and nonlinear features of ECG signals.
    Elhaj FA, Salim N, Harris AR, Swee TT, Ahmed T.
    Comput Methods Programs Biomed; 2016 Apr 19; 127():52-63. PubMed ID: 27000289
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  • 25. Robust electrocardiogram (ECG) beat classification using discrete wavelet transform.
    Minhas FU, Arif M.
    Physiol Meas; 2008 May 19; 29(5):555-70. PubMed ID: 18427158
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  • 27. QRS detection based on wavelet coefficients.
    Zidelmal Z, Amirou A, Adnane M, Belouchrani A.
    Comput Methods Programs Biomed; 2012 Sep 19; 107(3):490-6. PubMed ID: 22296976
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  • 30. Wavelet Scattering Transform for ECG Beat Classification.
    Liu Z, Yao G, Zhang Q, Zhang J, Zeng X.
    Comput Math Methods Med; 2020 Sep 19; 2020():3215681. PubMed ID: 33133225
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  • 33. Comparative study of morphological and time-frequency ECG descriptors for heartbeat classification.
    Christov I, Gómez-Herrero G, Krasteva V, Jekova I, Gotchev A, Egiazarian K.
    Med Eng Phys; 2006 Nov 19; 28(9):876-87. PubMed ID: 16476566
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  • 34. Block-based neural networks for personalized ECG signal classification.
    Jiang W, Kong SG.
    IEEE Trans Neural Netw; 2007 Nov 19; 18(6):1750-61. PubMed ID: 18051190
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  • 36. The morphological classification of heartbeats as dominant and non-dominant in ECG signals.
    Chiarugi F, Emmanouilidou D, Tsamardinos I.
    Physiol Meas; 2010 May 19; 31(5):611-31. PubMed ID: 20308771
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  • 37. Genetic algorithm for the optimization of features and neural networks in ECG signals classification.
    Li H, Yuan D, Ma X, Cui D, Cao L.
    Sci Rep; 2017 Jan 31; 7():41011. PubMed ID: 28139677
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  • 38. Feature extraction of ECG signal.
    Chandra S, Sharma A, Singh GK.
    J Med Eng Technol; 2018 May 31; 42(4):306-316. PubMed ID: 30251572
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  • 39. Adaptive Fourier decomposition based ECG denoising.
    Wang Z, Wan F, Wong CM, Zhang L.
    Comput Biol Med; 2016 Oct 01; 77():195-205. PubMed ID: 27568983
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