IDEAS home Printed from https://ideas.repec.org/a/taf/nmcmxx/v26y2020i2p193-203.html
   My bibliography  Save this article

Growth rate, growth curve and growth prediction of tumour in the competitive model

Author

Listed:
  • Mahdi Sohrabi-Haghighat
  • Atefeh Deris

Abstract

The growth of cancer is still the focus of many research works in the scientific community. So far, various models have been introduced to analyse the behaviour of cancers, including the mathematical growth models such as Logistic, Gompertz and Bertalany. Despite the advances in the analysis of the cancer behaviour, the lack of definitive treatment of cancer disease indicates the need for new perspectives which are supported by more biological background. Recently, a model has been proposed, in which, the tumour growth is interpreted as the outcome of the competition of healthy and cancer cells over the available oxygen, nutrients and space. We have modified this model in order to provide the necessary preparations for wider use of the model in growth rate, growth curve and growth prediction of tumours. Meanwhile, the model is performed on some experimental data to show its capabilities.

Suggested Citation

  • Mahdi Sohrabi-Haghighat & Atefeh Deris, 2020. "Growth rate, growth curve and growth prediction of tumour in the competitive model," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 26(2), pages 193-203, March.
    • Handle: RePEc:taf:nmcmxx:v:26:y:2020:i:2:p:193-203
    DOI: 10.1080/13873954.2020.1738498
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13873954.2020.1738498
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/13873954.2020.1738498?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:nmcmxx:v:26:y:2020:i:2:p:193-203. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/NMCM20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.