IDEAS home Printed from https://ideas.repec.org/a/ibn/masjnl/v4y2010i8p134.html
   My bibliography  Save this article

Feature Selection Algorithm using Fuzzy Rough Sets for Predicting Cervical Cancer Risks

Author

Listed:
  • Vandar Kuzhali Jagannathan
  • Rajendran Govind
  • Srinivasan V
  • Siva Kumar Ganapathi

Abstract

Early detection or prediction is very important to reduce the fatalities of Cervical Cancer. Cancer cells affect the Cervix area initially, and then it will spread near by parts. A method using Fuzzy Rough sets is used to analyze the demographic dataset and identify the risk of Cervical Cancer. This method integrates Entropy, Information Gain (IG) and Fuzzy Rough sets for identifying the risk of Cervical Cancer earlier. Risk Factors are identified by IG. Rules are extracted by Fuzzy Rough sets. These rules can be used to identify the risk of Cervical Cancer efficiently that the decision trees. It is found that Human Papilloma Virus (HPV) and having Multiple Sexual Partners (MP) are the major risk factors increase the chances of affecting this cancer. If all the above factors are high the risk of affecting Cervical Cancer is high. Result of this paper will help to improve the clinical practice guidance for analyzing the risk of Cervical Cancer.Keywords- Cervical Cancer, Entropy, Information Gain, Fuzzy Rough Sets, Demographic Data, Feature selection.

Suggested Citation

  • Vandar Kuzhali Jagannathan & Rajendran Govind & Srinivasan V & Siva Kumar Ganapathi, 2010. "Feature Selection Algorithm using Fuzzy Rough Sets for Predicting Cervical Cancer Risks," Modern Applied Science, Canadian Center of Science and Education, vol. 4(8), pages 134-134, August.
    • Handle: RePEc:ibn:masjnl:v:4:y:2010:i:8:p:134
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/mas/article/download/6192/5522
    Download Restriction: no
    File URL: https://ccsenet.org/journal/index.php/mas/article/view/6192
    Download Restriction: no
    ---><---

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:ibn:masjnl:v:4:y:2010:i:8:p:134. 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: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    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.