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Journal Abstract Search

770 related items for PubMed ID: 21852077

  • 1. Kernel machines for epilepsy diagnosis via EEG signal classification: a comparative study.
    Lima CA, Coelho AL.
    Artif Intell Med; 2011 Oct; 53(2):83-95. PubMed ID: 21852077
    [Abstract] [Full Text] [Related]

  • 2. Tackling EEG signal classification with least squares support vector machines: a sensitivity analysis study.
    Lima CA, Coelho AL, Eisencraft M.
    Comput Biol Med; 2010 Aug; 40(8):705-14. PubMed ID: 20621291
    [Abstract] [Full Text] [Related]

  • 3. Support vector machines for seizure detection in an animal model of chronic epilepsy.
    Nandan M, Talathi SS, Myers S, Ditto WL, Khargonekar PP, Carney PR.
    J Neural Eng; 2010 Jun; 7(3):036001. PubMed ID: 20404397
    [Abstract] [Full Text] [Related]

  • 4. [Application of SVM and wavelet analysis in EEG classification].
    Zhao J, Zhou W, Liu K, Cai D.
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2011 Apr; 28(2):277-9. PubMed ID: 21604484
    [Abstract] [Full Text] [Related]

  • 5. Hierarchical multi-class SVM with ELM kernel for epileptic EEG signal classification.
    Murugavel AS, Ramakrishnan S.
    Med Biol Eng Comput; 2016 Jan; 54(1):149-61. PubMed ID: 26296799
    [Abstract] [Full Text] [Related]

  • 6. Real-time epileptic seizure prediction using AR models and support vector machines.
    Chisci L, Mavino A, Perferi G, Sciandrone M, Anile C, Colicchio G, Fuggetta F.
    IEEE Trans Biomed Eng; 2010 May; 57(5):1124-32. PubMed ID: 20172805
    [Abstract] [Full Text] [Related]

  • 7. Analysis of EEG signals by combining eigenvector methods and multiclass support vector machines.
    Derya Ubeyli E.
    Comput Biol Med; 2008 Jan; 38(1):14-22. PubMed ID: 17651716
    [Abstract] [Full Text] [Related]

  • 8. Clustering technique-based least square support vector machine for EEG signal classification.
    Siuly, Li Y, Wen PP.
    Comput Methods Programs Biomed; 2011 Dec; 104(3):358-72. PubMed ID: 21168234
    [Abstract] [Full Text] [Related]

  • 9. Seizure prediction with spectral power of EEG using cost-sensitive support vector machines.
    Park Y, Luo L, Parhi KK, Netoff T.
    Epilepsia; 2011 Oct; 52(10):1761-70. PubMed ID: 21692794
    [Abstract] [Full Text] [Related]

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  • 13. Epileptic EEG classification based on extreme learning machine and nonlinear features.
    Yuan Q, Zhou W, Li S, Cai D.
    Epilepsy Res; 2011 Sep; 96(1-2):29-38. PubMed ID: 21616643
    [Abstract] [Full Text] [Related]

  • 14. Bayesian framework for least-squares support vector machine classifiers, gaussian processes, and kernel Fisher discriminant analysis.
    Van Gestel T, Suykens JA, Lanckriet G, Lambrechts A, De Moor B, Vandewalle J.
    Neural Comput; 2002 May; 14(5):1115-47. PubMed ID: 11972910
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  • 15. [The recognition methodology study of epileptic EEGs based on support vector machine].
    Huang R, Du S, Chen Z, Zhangzhen, Zhouyi.
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2013 Oct; 30(5):919-24. PubMed ID: 24459944
    [Abstract] [Full Text] [Related]

  • 16. Detection of seizures in EEG using subband nonlinear parameters and genetic algorithm.
    Hsu KC, Yu SN.
    Comput Biol Med; 2010 Oct; 40(10):823-30. PubMed ID: 20832782
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  • 19. Support vector machines for automated recognition of obstructive sleep apnea syndrome from ECG recordings.
    Khandoker AH, Palaniswami M, Karmakar CK.
    IEEE Trans Inf Technol Biomed; 2009 Jan; 13(1):37-48. PubMed ID: 19129022
    [Abstract] [Full Text] [Related]

  • 20. Automatic seizure detection using wavelet transform and SVM in long-term intracranial EEG.
    Liu Y, Zhou W, Yuan Q, Chen S.
    IEEE Trans Neural Syst Rehabil Eng; 2012 Nov; 20(6):749-55. PubMed ID: 22868635
    [Abstract] [Full Text] [Related]

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