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Experiment Design: Identification and Validation of Simple and Complex Models of Endocrine-Metabolic Systems

  • Claudio Cobelli
  • Karl Thomaseth
Conference paper
Part of the Lecture Notes in Biomathematics book series (LNBM, volume 57)

Abstract

Mathematical models in conjunction with dynamic input-output data are increasingly used in quantitative studies of endocrine-metabolic systems both in physiology and clinical medicine /1/.The purpose of modeling includes understanding, estimation of internal (non-measurable) parameters, diagnosis and control. Depending on the purpose of the study, models of different complexity are developed, and an essential role is played by identification and validation, respectively the determination of structure and parameter values and the assessment of whether or not the postulated model is adequate for its intended purpose.

Keywords

Fisher Information Matrix Sampling Schedule Optimal Input Optimal Experiment Design Identifiability Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1985

Authors and Affiliations

  • Claudio Cobelli
    • 1
  • Karl Thomaseth
    • 1
  1. 1.Istituto di Elettrotecnica e di ElettronicaUniversità di Padova and LADSEB-CNRPadovaItaly

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