Model Identification and Parameter Estimation

Andrzej Świerniak, Marek Kimmel, Jaroslaw Smieja, Krzysztof Puszynski and Krzysztof Psiuk-Maksymowicz
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Andrzej Świerniak: Silesian University of Technology, Institute of Automatic Control
Marek Kimmel: Silesian University of Technology, Institute of Automatic Control
Jaroslaw Smieja: Silesian University of Technology, Institute of Automatic Control
Krzysztof Puszynski: Silesian University of Technology, Institute of Automatic Control
Krzysztof Psiuk-Maksymowicz: Silesian University of Technology, Institute of Automatic Control

Chapter Chapter 6 in System Engineering Approach to Planning Anticancer Therapies, 2016, pp 171-198 from Springer

Abstract: Abstract Analysis of the models presented in the preceding chapters may be focused on drawing conclusions of either qualitative or quantitative nature. In the first case, parameter values are not needed, as the goal is to determine, for example, stability properties or the form of the optimal control. Such conclusions subsequently provide the basis for quantitative analysis that concerns a particular cancer type and attempts to determine the outcome of a therapy, or, in more advanced studies, the optimal therapy protocol. The latter is of more value from the clinical point of view. However, applicability of modeling results depends on the ability to estimate correct parameter values for the models under consideration. In subsequent sections, estimation of the model parameters is discussed in the context of experimental and numerical procedures, relevant for the models described in previous chapters.

Keywords: Sensitivity Function; Cell Cycle Phase; Fluorescence Recovery After Photobleaching; Fano Factor; Global Sensitivity Analysis (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-28095-0_6

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DOI: 10.1007/978-3-319-28095-0_6

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