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Related Experiment Videos

Mathematical modelling for the new millenium: medicine by numbers.

Stephen W Smye1, Richard H Clayton

  • 1Department of Medical Physics and Engineering, Leeds Teaching Hospitals, St James's University Hospital, Beckett Street, LS9 7TF, Leeds, UK. s.w.smye@leeds.ac.uk

Medical Engineering & Physics
|October 12, 2002
PubMed
Summary

Mathematical models offer rigor and utility, but their application in biology and medicine is limited by experimental challenges. This paper defines characteristics of a

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Area of Science:

  • * Mathematical modeling in life sciences.
  • * Interdisciplinary applications of quantitative methods.

Background:

  • * Historically, biology and medicine have lacked a strong mathematical formalism.
  • * Challenges include experimental measurement difficulties, signal noise, and sensor limitations.
  • * This has led to a relative paucity of mathematical models in these fields.

Purpose of the Study:

  • * To define the characteristics of a 'good' mathematical model.
  • * To encourage the development and application of models in new biological and medical areas.
  • * To outline future directions for mathematical modeling in these disciplines.

Main Methods:

  • * Defining principles of a 'good' model: accuracy, predictability, economy, uniqueness, and elegance.
  • * Illustrating these principles using four case studies.

Related Experiment Videos

  • * Discussing the integration of mathematical models with experimental and clinical research.

    • Main Results:

    • * Proposed criteria for evaluating mathematical models in biology and medicine.
    • * Demonstrated the utility of these criteria through diverse examples.
    • * Highlighted the potential for 'in silico' models to complement traditional research methods.

    Conclusions:

    • * A 'good' model in biology and medicine should be accurate, predictive, economical, unique, and elegant.
    • * Mathematical models are poised to become routine adjuncts to laboratory experiments and clinical trials.
    • * The future will see increased use of 'in silico' models in biological and medical research.