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Journal Abstract Search

183 related items for PubMed ID: 17287063

  • 1. Prediction of countershock success using single features from multiple ventricular fibrillation frequency bands and feature combinations using neural networks.
    Neurauter A, Eftestøl T, Kramer-Johansen J, Abella BS, Sunde K, Wenzel V, Lindner KH, Eilevstjønn J, Myklebust H, Steen PA, Strohmenger HU.
    Resuscitation; 2007 May; 73(2):253-63. PubMed ID: 17287063
    [Abstract] [Full Text] [Related]

  • 2. Prediction of countershock success employing single features from multiple ventricular fibrillation frequency bands and feature combinations using neural networks.
    Neurauter A, Strohmenger HU.
    Resuscitation; 2008 Jan; 76(1):152. PubMed ID: 17697741
    [No Abstract] [Full Text] [Related]

  • 3. Predicting defibrillation success.
    Strohmenger HU.
    Curr Opin Crit Care; 2008 Jun; 14(3):311-6. PubMed ID: 18467892
    [Abstract] [Full Text] [Related]

  • 4. Improving countershock success prediction during cardiopulmonary resuscitation using ventricular fibrillation features from higher ECG frequency bands.
    Neurauter A, Eftestøl T, Kramer-Johansen J, Abella BS, Wenzel V, Lindner KH, Eilevstjønn J, Myklebust H, Steen PA, Sterz F, Jahn B, Strohmenger HU.
    Resuscitation; 2008 Dec; 79(3):453-9. PubMed ID: 18954929
    [Abstract] [Full Text] [Related]

  • 5. Estimation of the duration of ventricular fibrillation using ECG single feature analysis.
    Neurauter A, Kramer-Johansen J, Eilevstjønn J, Myklebust H, Wenzel V, Lindner KH, Eftestøl T, Steen PA, Strohmenger HU.
    Resuscitation; 2007 May; 73(2):246-52. PubMed ID: 17368907
    [Abstract] [Full Text] [Related]

  • 6. Detrended fluctuation analysis predicts successful defibrillation for out-of-hospital ventricular fibrillation cardiac arrest.
    Lin LY, Lo MT, Ko PC, Lin C, Chiang WC, Liu YB, Hu K, Lin JL, Chen WJ, Ma MH.
    Resuscitation; 2010 Mar; 81(3):297-301. PubMed ID: 20071067
    [Abstract] [Full Text] [Related]

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  • 9. A probabilistic neural network as the predictive classifier of out-of-hospital defibrillation outcomes.
    Yang Z, Yang Z, Lu W, Harrison RG, Eftestøl T, Steen PA.
    Resuscitation; 2005 Jan; 64(1):31-6. PubMed ID: 15629552
    [Abstract] [Full Text] [Related]

  • 10. Using within-patient correlation to improve the accuracy of shock outcome prediction for cardiac arrest.
    Gundersen K, Kvaløy JT, Kramer-Johansen J, Olasveengen TM, Eilevstjønn J, Eftestøl T.
    Resuscitation; 2008 Jul; 78(1):46-51. PubMed ID: 18485562
    [Abstract] [Full Text] [Related]

  • 11. The frequency ratio: an improved method to estimate ventricular fibrillation duration based on Fourier analysis of the waveform.
    Sherman LD.
    Resuscitation; 2006 Jun; 69(3):479-86. PubMed ID: 16563594
    [Abstract] [Full Text] [Related]

  • 12. Independent evaluation of a defibrillation outcome predictor for out-of-hospital cardiac arrested patients.
    Eftestøl T, Losert H, Kramer-Johansen J, Wik L, Sterz F, Steen PA.
    Resuscitation; 2005 Oct; 67(1):55-61. PubMed ID: 16154680
    [Abstract] [Full Text] [Related]

  • 13. Predicting defibrillation success in sudden cardiac arrest patients.
    Firoozabadi R, Nakagawa M, Helfenbein ED, Babaeizadeh S.
    J Electrocardiol; 2013 Oct; 46(6):473-9. PubMed ID: 23871657
    [Abstract] [Full Text] [Related]

  • 14. Irregularity test for very short electrocardiogram (ECG) signals as a method for predicting a successful defibrillation in patients with ventricular fibrillation.
    Jagric T, Marhl M, Stajer D, Kocjancic ST, Jagric T, Podbregar M, Perc M.
    Transl Res; 2007 Mar; 149(3):145-51. PubMed ID: 17320800
    [Abstract] [Full Text] [Related]

  • 15. Improved prediction of defibrillation success for out-of-hospital VF cardiac arrest using wavelet transform methods.
    Watson JN, Uchaipichat N, Addison PS, Clegg GR, Robertson CE, Eftestol T, Steen PA.
    Resuscitation; 2004 Dec; 63(3):269-75. PubMed ID: 15582761
    [Abstract] [Full Text] [Related]

  • 16. Shock outcome is related to prior rhythm and duration of ventricular fibrillation.
    Eilevstjønn J, Kramer-Johansen J, Sunde K.
    Resuscitation; 2007 Oct; 75(1):60-7. PubMed ID: 17467139
    [Abstract] [Full Text] [Related]

  • 17. Electrical defibrillation outcome prediction by waveform analysis of ventricular fibrillation in cardiac arrest out of hospital patients.
    Nakagawa Y, Sato Y, Kojima T, Wakabayashi T, Morita S, Amino M, Inokuchi S.
    Tokai J Exp Clin Med; 2012 Apr 20; 37(1):1-5. PubMed ID: 22488555
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  • 19. Prediction of countershock success: a comparison of autoregressive and fast fourier transformed spectral estimators.
    Nowak CN, Fischer G, Neurauter A, Wieser L, Strohmenger HU.
    Methods Inf Med; 2009 Apr 20; 48(5):486-92. PubMed ID: 19448883
    [Abstract] [Full Text] [Related]

  • 20. The predictive value of ventricular fibrillation electrocardiogram signal frequency and amplitude variables in patients with out-of-hospital cardiac arrest.
    Strohmenger HU, Eftestol T, Sunde K, Wenzel V, Mair M, Ulmer H, Lindner KH, Steen PA.
    Anesth Analg; 2001 Dec 20; 93(6):1428-33, table of contents. PubMed ID: 11726418
    [Abstract] [Full Text] [Related]

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