• Login
    • Library Home
    View Item 
    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Identification of childhood leukemia using deep learning

    Thumbnail
    View/Open
    13101235_CSE.pdf (1.056Mb)
    Date
    2017
    Publisher
    BRAC University
    Author
    Tultul, Farana Naz
    Metadata
    Show full item record
    URI
    http://hdl.handle.net/10361/8888
    Abstract
    Although cancer in children is rare, it is the leading cause of death past infancy amongst children. According to Afshar, Abdolrahmani, Tanha, Seif, Taheri(2010), Leukemia or blood cancer is one of the most common cancers in children, comprising of more than a third of all childhood cancers. Despite the advances of technology and research and overall decrease in mortality, nearly 2000 children die of cancer each year in the United States according to www.cancer.gov(2017). The website also tells us that if Leukemia cases are identified late or proper treatment isn’t applied, then it can be mortal. For this reason, we have decided to use deep learning for the rapid identification of leukemia in the absence of doctors, which can be done in clinics by present nurses and lab workers. We are going to use ID3 and C4.5 (extension of ID3) classifiers, Naïve Bayes and Multi-layer Perceptron (MLP) Neural network on the data I have gathered of the 78 cases and check which one gives the most accurate result.
    Keywords
    Leukemia; Neural network; Childhood leukemia; Naïve bayes; MLP
     
    Description
    This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.
     
    Cataloged from PDF version of thesis report.
     
    Includes bibliographical references (page 28).
    Department
    Department of Computer Science and Engineering, BRAC University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

    Copyright © 2008-2019 Ayesha Abed Library, Brac University 
    Contact Us | Send Feedback
     

     

    Policy Guidelines

    • BracU Policy
    • Publisher Policy

    Browse

    All of BracU Institutional RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    Copyright © 2008-2019 Ayesha Abed Library, Brac University 
    Contact Us | Send Feedback