These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

378 related articles for article (PubMed ID: 18228143)

  • 21. Complexity and nonlinearity in short-term heart period variability: comparison of methods based on local nonlinear prediction.
    Porta A; Guzzetti S; Furlan R; Gnecchi-Ruscone T; Montano N; Malliani A
    IEEE Trans Biomed Eng; 2007 Jan; 54(1):94-106. PubMed ID: 17260860
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Bivariate nonlinear prediction to quantify the strength of complex dynamical interactions in short-term cardiovascular variability.
    Faes L; Nollo G
    Med Biol Eng Comput; 2006 May; 44(5):383-92. PubMed ID: 16937180
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Detection of nonlinearity in cardiovascular variability signals using cyclostationary analysis.
    Seydnejad S
    Ann Biomed Eng; 2007 May; 35(5):744-54. PubMed ID: 17372836
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Linear and nonlinear ARMA model parameter estimation using an artificial neural network.
    Chon KH; Cohen RJ
    IEEE Trans Biomed Eng; 1997 Mar; 44(3):168-74. PubMed ID: 9216130
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Accounting for respiration is necessary to reliably infer Granger causality from cardiovascular variability series.
    Porta A; Bassani T; Bari V; Pinna GD; Maestri R; Guzzetti S
    IEEE Trans Biomed Eng; 2012 Mar; 59(3):832-41. PubMed ID: 22194232
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Does well-harmonized homeostasis exist in heart rate fluctuations? Time series analysis and model simulations.
    Shiau YH
    Auton Neurosci; 2009 Mar; 146(1-2):62-9. PubMed ID: 19162560
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Comparing generalized and phase synchronization in cardiovascular and cardiorespiratory signals.
    Pereda E; De la Cruz DM; De Vera L; González JJ
    IEEE Trans Biomed Eng; 2005 Apr; 52(4):578-83. PubMed ID: 15825859
    [TBL] [Abstract][Full Text] [Related]  

  • 28. A parametric method to measure time-varying linear and nonlinear causality with applications to EEG data.
    Zhao Y; Billings SA; Wei HL; Sarrigiannis PG
    IEEE Trans Biomed Eng; 2013 Nov; 60(11):3141-8. PubMed ID: 23797214
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Testing for directed influences among neural signals using partial directed coherence.
    Schelter B; Winterhalder M; Eichler M; Peifer M; Hellwig B; Guschlbauer B; Lücking CH; Dahlhaus R; Timmer J
    J Neurosci Methods; 2006 Apr; 152(1-2):210-9. PubMed ID: 16269188
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Cardiovascular control and time domain Granger causality: insights from selective autonomic blockade.
    Porta A; Castiglioni P; Di Rienzo M; Bassani T; Bari V; Faes L; Nollo G; Cividjan A; Quintin L
    Philos Trans A Math Phys Eng Sci; 2013 Aug; 371(1997):20120161. PubMed ID: 23858489
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Development of interaction measures based on adaptive non-linear time series analysis of biomedical signals.
    Leistritz L; Hesse W; Arnold M; Witte H
    Biomed Tech (Berl); 2006 Jul; 51(2):64-9. PubMed ID: 16915767
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Spectral decomposition in multichannel recordings based on multivariate parametric identification.
    Baselli G; Porta A; Rimoldi O; Pagani M; Cerutti S
    IEEE Trans Biomed Eng; 1997 Nov; 44(11):1092-101. PubMed ID: 9353988
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Multichannel least-squares linear regression provides a fast, accurate, unbiased and robust estimation of Granger causality for neurophysiological data.
    Frye RE; Wu MH
    Comput Biol Med; 2011 Dec; 41(12):1118-31. PubMed ID: 21640990
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Non-linear dynamics of cardiovascular system in humans exposed to repetitive apneas modeling obstructive sleep apnea: aggregated time series data analysis.
    Trzebski A; Smietanowski M
    Auton Neurosci; 2001 Jul; 90(1-2):106-15. PubMed ID: 11485276
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Analysis of the QT-RR variability interactions using the NARMAX model.
    Baakek YN; Bereksi Reguig F; Hadj Slimane ZE
    J Med Eng Technol; 2013 Jan; 37(1):48-55. PubMed ID: 23249306
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Robust algorithm for estimation of time-varying transfer functions.
    Zou R; Chon KH
    IEEE Trans Biomed Eng; 2004 Feb; 51(2):219-28. PubMed ID: 14765694
    [TBL] [Abstract][Full Text] [Related]  

  • 37. A stochastic nonlinear autoregressive algorithm reflects nonlinear dynamics of heart-rate fluctuations.
    Armoundas AA; Ju K; Iyengar N; Kanters JK; Saul PJ; Cohen RJ; Chon KH
    Ann Biomed Eng; 2002 Feb; 30(2):192-201. PubMed ID: 11962771
    [TBL] [Abstract][Full Text] [Related]  

  • 38. A nonlinear causality measure in the frequency domain: nonlinear partial directed coherence with applications to EEG.
    He F; Billings SA; Wei HL; Sarrigiannis PG
    J Neurosci Methods; 2014 Mar; 225():71-80. PubMed ID: 24472530
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Real-time lumped parameter modeling of cardiovascular dynamics using electrocardiogram signals: toward virtual cardiovascular instruments.
    Le TQ; Bukkapatnam ST; Komanduri R
    IEEE Trans Biomed Eng; 2013 Aug; 60(8):2350-60. PubMed ID: 23559024
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Granger causality in cardiovascular variability series: comparison between model-based and model-free approaches.
    Porta A; Bassani T; Bari V; Guzzetti S
    Annu Int Conf IEEE Eng Med Biol Soc; 2012; 2012():3684-7. PubMed ID: 23366727
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 19.