Medical diagnosis using data mining techniques / Shaiful Nizam Zamri

Shaiful Nizam , Zamri (2003) Medical diagnosis using data mining techniques / Shaiful Nizam Zamri. Undergraduates thesis, University of Malaya.

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    Medical Diagnosis Using Data Mining Techniques is a system in specifically facilitates the data mining techniques in predicting the appropriate drug prescription of certain condition of patients. The report will firstly cover the inductors of data mining and the overview of the overall system and it also reviewed about the data mining paradigm. Secondly, this report will review the literature part which started with basic knowledge of data mining and knowing what the basic information about data mining. At the end of this part will reviewed and studied about the mining algorithm the gathered from the research made earlier. Then followed by the methodology part as the scenario of the project and the system analysis, which will review the need requirements and tools used to implement the system. The system design part will explains the flow and functionality of the system structure. Then, the system implementation part explains the selected tools chosen for implementing the system which using the Clementine Data Mining Solution. System testing the was done for checking and detecting error or malfunction of the system. The final part is generally the overall system evaluation and the conclusion of the whole project which explains the strength and the limitation of the system.

    Item Type: Thesis ( Undergraduates)
    Additional Information: Academic Exercise (Bachelor’s Degree) – Faculty of Computer Science & Information Technology, University of Malaya, 2002/2003.
    Uncontrolled Keywords: Data Mining Techniques; Algorithm; Drug prescription
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Q Science > QA Mathematics > QA76 Computer software
    Divisions: Faculty of Computer Science & Information Technology
    Depositing User: Mr Mohd Zaimi Izwan Kamarunsaman
    Date Deposited: 10 May 2020 14:44
    Last Modified: 10 May 2020 14:44

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