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On the evolution of the physiological model.

W S Yamamoto, E S Walton

    Annual Review of Biophysics and Bioengineering
    |January 1, 1975
    PubMed
    Summary
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    Future models in respiratory physiology require programs that can explain findings and synthesize information. This evolution will enable better tools for physiology, medical diagnosis, and scholarly reviews.

    Area of Science:

    • Computational Biology
    • Physiology
    • Artificial Intelligence

    Background:

    • Computerized mathematical models are increasingly used in respiratory physiology.
    • Current models show advanced subject control but lack mechanization for explanatory potential.
    • There is a growing interest in the expository function of models within the scientific community.

    Purpose of the Study:

    • To outline the future evolution of the expository function of computerized mathematical models.
    • To explore the mechanization of the purposes and philosophical potential of automata in physiological modeling.
    • To identify the next major evolutionary step in machine-based "explanation" for scientific models.

    Main Methods:

    • Analysis of current trends in respiratory physiology models.

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  • Conceptualization of program-making programs for deductive inference and explanation.
  • Investigation of formalizing rules for traversing between model planes and understanding "second order" effects.
  • Main Results:

    • The evolution of models necessitates program-making programs capable of aggregation for inference and top-down explanation.
    • Establishing rules for identifying "second order" effects is crucial for model traversal.
    • Models must develop the capacity to ignore, "forget," and gloss over information to become useful tools.

    Conclusions:

    • The next evolutionary step for models is the pursuit of machine-based "explanation."
    • Future models will require sophisticated programs to manage information synthesis and deductive reasoning.
    • Enhanced models will provide better tools for informed action in physiology, medical diagnosis, and scientific review writing.