• DocumentCode
    3728329
  • Title

    Tumor Model Identification and Statistical Analysis

  • Author

    S?pi;Tam?s ;D?niel Andr?s ; Kov?cs

  • Author_Institution
    Physiol. Controls Group, Obuda Univ., Budapest, Hungary
  • fYear
    2015
  • Firstpage
    2481
  • Lastpage
    2486
  • Abstract
    Tumor growth model identification under antiangiogenic therapy is a very current issue since the existing models in the literature have some limitations and usually they are not clinically validated. We have carried out animal experiments to observe valid data, mice were transplanted with C38 colon Aden carcinoma and they were treated with bevacizumab. Two groups were created, control group was treated according to the protocol, while case group members receive much lower doses daily. We created fixed and mixed models for the groups. Mixed models differs from fixed ones in random effects -- in the case of mixed models both the intercept and the slope are random variables. These models are appropriate when the aim is to model not the concrete subjects in the sample, but rather, to describe the imagined population from which the samples were coming.
  • Keywords
    "Tumors","Magnetic resonance imaging","Volume measurement","Biological system modeling","Mice","Mathematical model"
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/SMC.2015.434
  • Filename
    7379566