IDEAS home Printed from https://ideas.repec.org/a/wsi/nmncxx/v16y2020i01ns1793005720500106.html
   My bibliography  Save this article

Fuzzy Expert System for Prediction of Prostate Cancer

Author

Listed:
  • Juthika Mahanta

    (Department of Mathematics, National Institute of Technology Silchar, Silchar, Cachar, Assam 788010, India)

  • Subhasis Panda

    (Department of Physics, National Institute of Technology Silchar, Silchar, Cachar, Assam 788010, India)

Abstract

A fuzzy expert system (FES) for the prediction of prostate cancer (PC) is prescribed in this paper. Age, prostate-specific antigen (PSA), prostate volume (PV) and % Free PSA (%FPSA) are fed as inputs into the FES and prostate cancer risk (PCR) is obtained as the output. Using knowledge-based rules in Mamdani type inference method the output is calculated. If PCR ≥50%, then the patient shall be advised to go for a biopsy test for confirmation. The efficacy of the designed FES is tested against a clinical dataset. The true prediction for all the patients turns out to be 68.91% whereas only for positive biopsy cases it rises to 73.77%. This simple yet effective FES can be used as supportive tool for decision-making in medical diagnosis.

Suggested Citation

  • Juthika Mahanta & Subhasis Panda, 2020. "Fuzzy Expert System for Prediction of Prostate Cancer," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 16(01), pages 163-176, March.
    • Handle: RePEc:wsi:nmncxx:v:16:y:2020:i:01:n:s1793005720500106
    DOI: 10.1142/S1793005720500106
    as

    Download full text from publisher

    File URL: https://www.worldscientific.com/doi/abs/10.1142/S1793005720500106
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S1793005720500106?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.

    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:wsi:nmncxx:v:16:y:2020:i:01:n:s1793005720500106. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/nmnc/nmnc.shtml .

    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.