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Journal Abstract Search

239 related items for PubMed ID: 21604488

  • 1. [Cardiac arrhythmia classification based on multi-features and support vector machines].
    Zhao Y, Hong W, Sun S.
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2011 Apr; 28(2):292-5. PubMed ID: 21604488
    [Abstract] [Full Text] [Related]

  • 2. Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal.
    Asl BM, Setarehdan SK, Mohebbi M.
    Artif Intell Med; 2008 Sep; 44(1):51-64. PubMed ID: 18585905
    [Abstract] [Full Text] [Related]

  • 3. Classification of the electrocardiogram signals using supervised classifiers and efficient features.
    Zadeh AE, Khazaee A, Ranaee V.
    Comput Methods Programs Biomed; 2010 Aug; 99(2):179-94. PubMed ID: 20510478
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  • 4. Cardiac arrhythmia classification using neural networks.
    Al-Nashash H.
    Technol Health Care; 2000 Aug; 8(6):363-72. PubMed ID: 11258582
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  • 5. Medical Decision Support System for Diagnosis of Heart Arrhythmia using DWT and Random Forests Classifier.
    Alickovic E, Subasi A.
    J Med Syst; 2016 Apr; 40(4):108. PubMed ID: 26922592
    [Abstract] [Full Text] [Related]

  • 6. Heartbeat classification using morphological and dynamic features of ECG signals.
    Ye C, Kumar BV, Coimbra MT.
    IEEE Trans Biomed Eng; 2012 Oct; 59(10):2930-41. PubMed ID: 22907960
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  • 10. Feature extraction for ECG heartbeats using higher order statistics of WPD coefficients.
    Kutlu Y, Kuntalp D.
    Comput Methods Programs Biomed; 2012 Mar; 105(3):257-67. PubMed ID: 22055998
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  • 12. Correlation technique and least square support vector machine combine for frequency domain based ECG beat classification.
    Dutta S, Chatterjee A, Munshi S.
    Med Eng Phys; 2010 Dec; 32(10):1161-9. PubMed ID: 20833096
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  • 13. A multi-stage automatic arrhythmia recognition and classification system.
    Kutlu Y, Kuntalp D.
    Comput Biol Med; 2011 Jan; 41(1):37-45. PubMed ID: 21183163
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  • 14. Cardiac arrhythmia beat classification using DOST and PSO tuned SVM.
    Raj S, Ray KC, Shankar O.
    Comput Methods Programs Biomed; 2016 Nov; 136():163-77. PubMed ID: 27686713
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  • 15. Arrhythmia detection and classification using morphological and dynamic features of ECG signals.
    Ye C, Coimbra MT, Vijaya Kumar BK.
    Annu Int Conf IEEE Eng Med Biol Soc; 2010 Nov; 2010():1918-21. PubMed ID: 21097000
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  • 17. Arrhythmia Classification of ECG Signals Using Hybrid Features.
    Anwar SM, Gul M, Majid M, Alnowami M.
    Comput Math Methods Med; 2018 Nov; 2018():1380348. PubMed ID: 30538768
    [Abstract] [Full Text] [Related]

  • 18. Combining Low-dimensional Wavelet Features and Support Vector Machine for Arrhythmia Beat Classification.
    Qin Q, Li J, Zhang L, Yue Y, Liu C.
    Sci Rep; 2017 Jul 20; 7(1):6067. PubMed ID: 28729684
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  • 19. A robust wavelet-based multi-lead Electrocardiogram delineation algorithm.
    Ghaffari A, Homaeinezhad MR, Akraminia M, Atarod M, Daevaeiha M.
    Med Eng Phys; 2009 Dec 20; 31(10):1219-27. PubMed ID: 19692287
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  • 20. Optimal delineation of ambulatory holter ECG events via false-alarm bounded segmentation of a wavelet-based principal components analyzed decision statistic.
    Homaeinezhad MR, Ghaffari A, Toosi HN, Tahmasebi M, Daevaeiha MM.
    Cardiovasc Eng; 2010 Sep 20; 10(3):136-56. PubMed ID: 20821349
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