A novel approach for cancer outcome prediction using personalized classifier

Md Jamiul Jahid, Jianhua Ruan

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Cancer patients can be classifier into different subtypes but an obvious question can ask, whether these predefined subtypes can be helpful to detect the risk of disease in advance which is a well known problem in cancer biology. In this article we address these issues of using subtypes for disease outcome prediction and propose a personalized classification approach by relaxing the predefined subtype idea. Finally, we find that our proposed method is helpful to develop prediction model which can be useful in clinical practice to predict disease outcome. Thus the idea proposed here has better accuracy and application than conventional approaches for cancer outcome prediction.

    Original languageEnglish (US)
    Title of host publicationProceeding of the 2012 ACM Research in Applied Computation Symposium, RACS 2012
    Pages72-73
    Number of pages2
    DOIs
    StatePublished - Dec 1 2012
    Event2012 ACM Research in Applied Computation Symposium, RACS 2012 - San Antonio, TX, United States
    Duration: Oct 23 2012Oct 26 2012

    Publication series

    NameProceeding of the 2012 ACM Research in Applied Computation Symposium, RACS 2012

    Conference

    Conference2012 ACM Research in Applied Computation Symposium, RACS 2012
    Country/TerritoryUnited States
    CitySan Antonio, TX
    Period10/23/1210/26/12

    Keywords

    • Outcome prediction
    • Personalized classification
    • Subtype

    ASJC Scopus subject areas

    • Computational Theory and Mathematics

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