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    A Bibliographic Overview of Colorectal Cancer Detection and Prevention Using Machine Learning Techniques

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    File(s)
    BourgetSpr22.pdf (1.928Mb)
    Date
    2022-04
    Author
    Bourget, Elena
    Mahan, Oliver
    Fenno, Emily
    Islam, Rakib
    Metadata
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    Abstract
    The idea of using machine learning techniques to identify colorectal cancer is a relatively new one, with most of the research being done in the last ten years. To determine the current state of research in this field, an analysis of a large number of research articles from Web of Science was performed. We aim to provide a comprehensive summary of the current state of colorectal cancer identification and prevention in order to understand the trend of research topics in the research domain. We do this through bibliographic analysis using VOSviewer, an automated visualization tool, on a variety of parameters. Our study will provide a foundation on which future research in the field of colorectal cancer detection and prevention using machine learning can be conducted.
    Subject
    Machine learning
    Cancer detection
    Colorectal cancer
    Bibliographic analysis
    Posters
    Department of Computer Science
    Permanent Link
    http://digital.library.wisc.edu/1793/84026
    Description
    Color poster with text and diagrams
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    • Student Research Day

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