IDEAS home Printed from https://ideas.repec.org/a/ids/wremsd/v19y2023i1-2p47-70.html
   My bibliography  Save this article

A study on impact of ageing population on Singapore healthcare systems using machine learning algorithms

Author

Listed:
  • Girija Periyasamy
  • Easwaramoorthy Rangaswamy
  • Uma Rani Srinivasan

Abstract

Ageing population has been identified as a key issue for healthcare because of its adverse impact on ageing and facilities of healthcare systems. The study is focused on ageing population which has been having widespread consequences in Singapore context. Review of the healthcare systems was done as the gap revealed the need to address the objectives of the study which is to evaluate the various improvements of healthcare systems in Singapore with respect to the ageing population requirements and analyse the various factors related to ageing population that influences the healthcare systems in Singapore. Analysis included ANOVA, Correlation, along with Machine Learning Algorithms like Decision Tree, Support Vector Machine and Logistic Regression. The results, discussions along with findings are also provided with links to the literature and research objectives. Suggestions were provided for various healthcare systems initiatives and needs that are required to transform to cope with ageing population.

Suggested Citation

  • Girija Periyasamy & Easwaramoorthy Rangaswamy & Uma Rani Srinivasan, 2023. "A study on impact of ageing population on Singapore healthcare systems using machine learning algorithms," World Review of Entrepreneurship, Management and Sustainable Development, Inderscience Enterprises Ltd, vol. 19(1/2), pages 47-70.
  • Handle: RePEc:ids:wremsd:v:19:y:2023:i:1/2:p:47-70
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=127243
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    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:ids:wremsd:v:19:y:2023:i:1/2:p:47-70. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=173 .

    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.