• DocumentCode
    2489435
  • Title

    Regression methods for parameter sensitivity analysis: Applications to cardiac arrhythmia mechanisms

  • Author

    Sobie, Eric A. ; Sarkar, Amrita X.

  • Author_Institution
    Dept. of Pharmacology & Syst. Therapeutics, Mount Sinai Sch. of Med., New York, NY, USA
  • fYear
    2011
  • fDate
    Aug. 30 2011-Sept. 3 2011
  • Firstpage
    4657
  • Lastpage
    4660
  • Abstract
    Mathematical models are used extensively in studies of cardiac electrophysiology and arrhythmia mechanisms. Models can generate novel predictions, suggest experiments, and provide a quantitative understanding of underlying mechanisms. Limitations of present modeling approaches, however, include non-uniqueness of both parameters and the models themselves, and difficulties in accounting for experimental variability. We describe new approaches that can begin to address these limitations, and show how these can provide novel insight into mathematical models of cardiac myocytes.
  • Keywords
    bioelectric phenomena; cardiology; diseases; physiological models; regression analysis; sensitivity analysis; cardiac arrhythmia mechanism; cardiac electrophysiology; cardiac myocytes; mathematical model; parameter sensitivity analysis; regression method; Analytical models; Biological system modeling; Computational modeling; Data models; Mathematical model; Predictive models; Transient analysis; Arrhythmias, Cardiac; Humans; Regression Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
  • Conference_Location
    Boston, MA
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4121-1
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2011.6091153
  • Filename
    6091153