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Primary Approach for Fraud Detection of Health Care Using Data Mining Techniques

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dc.contributor.author Osman, Maha Osman Mohamed
dc.date.accessioned 2018-12-13T12:09:20Z
dc.date.available 2018-12-13T12:09:20Z
dc.date.issued 2005-08
dc.identifier.uri http://repo.uofg.edu.sd/handle/123456789/3221
dc.description A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in Computer Science and Information Department of Computer Engineering ,Faculty of Engineering and Technology,University of Gezira,August 2005, en_US
dc.description.abstract Data mining is one of the fastest growing fields in the computer industry; one of the greatest strengths of data mining is reflected in its wide range of methodologies and techniques that can be applied to a host of problem sets. The major advantage that data mining tools have over the traditional analysis tools is that they use computer cycles to replace human cycles. Patient health records represent comprehensive documents of the continuity of heath care and are a rich source of data for research. Data are generally accessible, accurate, and relatively inexpensive. This research use data mining techniques to detect fraud from patients and providers .To detects those fraud we use combination of PolyAnalyst techniques. We detect fraud from patients by performing analysis to the database and then create link chart, also we can detect fraud from providers by Transition Basket Analysis. By performing those techniques we minimize the frauds from both patients and providers. en_US
dc.description.sponsorship Moawia Elfaki Yahia Aldaw (Supervisor) en_US
dc.language.iso en en_US
dc.publisher University of Gezira en_US
dc.subject Technology en_US
dc.subject computer en_US
dc.subject Medicines en_US
dc.subject Banking en_US
dc.title Primary Approach for Fraud Detection of Health Care Using Data Mining Techniques en_US
dc.type Thesis en_US


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