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Applying data mining in medical data with focus on mortality related to accident in children

Saraee, M, Ehghaghi, Z, Meamarzadeh, H and Zibanezhad, B 2008, Applying data mining in medical data with focus on mortality related to accident in children , in: IEEE International Multitopic Conference, 23-24 December 2008, Karachi, Pakistan.

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    Abstract

    Trauma is the main leading cause of death in children; we need a tool to prevent and predict the outcome in these patients. Data mining is the science of extracting the useful information from a large amount of data sets or databases that leads to statistical and logical analysis and looking for patterns that could help the decision makers. In This paper we offer an approach for using data mining in classifying mortality rate related to accidents in children under 15. These data were gathered from the patient files which were recorded in the medical record section of the Alzahra Hospital in Isfahan. The data mining methods in use are decision tree and Bayes' theorem. Applying DM techniques to the data brings about very interesting and valuable results. It is concluded that in this case, comparing the result of evaluating the models on test set, decision tree works better than Bayes' theorem. In this paper, we have used Clementine 12.0 for creating the models.

    Item Type: Conference or Workshop Item (Paper)
    Themes: Health and Wellbeing
    Schools: Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering > Data Mining and Pattern Recognition Research Centre
    Journal or Publication Title: Proceedings of IEEE International Multitopic Conference
    Publisher: IEEE
    Refereed: Yes
    Related URLs:
    Depositing User: Dr Mo Saraee
    Date Deposited: 27 Oct 2011 10:50
    Last Modified: 20 Aug 2013 18:16
    URI: http://usir.salford.ac.uk/id/eprint/18703

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