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    Computational Physiology

    Simula Summer School 2022 − Student Reports

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    Contributor(s)
    McCabe, Kimberly J. (editor)
    Language
    English
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    Abstract
    This open access volume compiles student reports from the 2022 Simula Summer School in Computational Physiology. The reports provide an overview of some tools available to model physiology in excitable tissues across scales and scientific questions. In 2022, Simula held the eighth annual Summer School in Computational Physiology in collaboration with the University of Oslo (UiO) and the University of California, San Diego (UCSD). Each year, the course focuses on modeling excitable tissues, with a special interest in cardiac physiology and neuroscience. Group research projects conducted by graduate students from around the world result in reports addressing problems of physiological importance. Reports may not necessarily represent new scientific results; rather, they can reproduce or supplement earlier studies. Reports from seven of the summer projects are included as separate chapters. The topics represented include multiscale mechanics, electrophysiology, pharmacology, and machine learning.
    URI
    https://library.oapen.org/handle/20.500.12657/61895
    Keywords
    Computational Physiology; Scientific computing; Electrophysiology; Electromechanics; Pharmacology; Cardiac Mechanics; Machine learning; Fluid mechanics; Bioengineering; Numerical analysis
    DOI
    10.1007/978-3-031-25374-4
    ISBN
    9783031253744, 9783031253744
    Publisher
    Springer Nature
    Publisher website
    https://www.springernature.com/gp/products/books
    Publication date and place
    Cham, 2023
    Imprint
    Springer Nature Switzerland
    Series
    Simula SpringerBriefs on Computing; Reports on Computational Physiology, 13
    Classification
    Maths for scientists
    Pages
    109
    Rights
    http://creativecommons.org/licenses/by/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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