• Login
    View Item 
    •   Home
    • Research from April 2016
    • Computing
    • View Item
    •   Home
    • Research from April 2016
    • Computing
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of UOBREPCommunitiesTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournalDepartmentThis CollectionTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournalDepartment

    My Account

    LoginRegister

    About

    AboutLearning ResourcesResearch Graduate SchoolResearch InstitutesUniversity Website

    Statistics

    Display statistics

    Analyse lifestyle related prostate cancer risk factors retrieved from literacy

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Authors
    Effiok, Emmanuel
    Liu, Enjie
    Hitchcock, Jonathan James
    Affiliation
    University of Bedfordshire
    Issue Date
    2018-02-01
    Subjects
    apriori algorithm
    knowledge extraction
    association rule mining
    risk factor
    
    Metadata
    Show full item record
    Abstract
    Risk factors for prostate cancer were identified through extensive research of literature and data was retrieved from both literatures and repositories. The research applies data mining techniques to the medical literatures and evidences on prostate cancer, with the aim to unravel the relationships between the presence of having multiple lifestyle factors and prostate cancer effective of occurrence of multiple factors. The research is to establish a possible predictive model based on theorized and proven risk factors and associations used in prostate cancer research. This paper describes the use of data mining algorithms on the risk factors to identify hidden knowledge. Firstly, an association rule mining algorithm is employed to identify the significant risk factors for the predictive modeling, based on the support level in terms of research materials used and confidence values. Secondly, the chosen factors were combined, modelled and visually represented to show their probability risks in relation to each other and the disease.
    Citation
    Effiok E., Liu E., Hitchcock J. (2018) 'Analyse lifestyle related prostate cancer risk factors retrieved from literacy', 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) - Exeter, Institute of Electrical and Electronics Engineers Inc..
    Publisher
    Institute of Electrical and Electronics Engineers Inc.
    URI
    http://hdl.handle.net/10547/623865
    DOI
    10.1109/iThings-GreenCom-CPSCom-SmartData.2017.174
    Additional Links
    https://ieeexplore.ieee.org/document/8276897
    Type
    Conference papers, meetings and proceedings
    Language
    en
    ISBN
    9781538630655
    ae974a485f413a2113503eed53cd6c53
    10.1109/iThings-GreenCom-CPSCom-SmartData.2017.174
    Scopus Count
    Collections
    Computing

    entitlement

     
    DSpace software (copyright © 2002 - 2021)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.