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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/98386

    Title: The Irrelevant Values Problem of Decision Tree in Medical Examination
    Authors: Chou, Kuang-Yi;Keh, Huan-Chao;Huang, Nan-Ching;Lu, Shing-Hwa;Chiang, Ding-An;Cheng, Yuan-Cheng
    Contributors: 淡江大學資訊工程學系
    Keywords: Decision Tree;Classification;Irrelevant Values;Missing Branches;Medical Examination
    Date: 2012-01-01
    Issue Date: 2014-07-24 13:59:30 (UTC+8)
    Publisher: 新北市:淡江大學
    Abstract: Data mining technique is extensively used in medical application. One of key tools is the decision tree. When a decision tree is represented by a collection of rules, the antecedents of individual rules may contain irrelevant values problem. When we use this complete set of rules to medical examinations, the irrelevant values problem may cause unnecessary economic burden both to the patient and the society. We used a hypothyroid disease as an example for the study of irrelevant values problem of decision tree in medical examination. Hypothyroid disease is used to associate to the mechanism of thyroid-stimulating hormone (TSH). Physicians will combine lots of information; such as patient's clinical records, medical images, and symptoms, prior to the final diagnosis and treatment, especially surgical operation. Therefore, to avoid generating rules with irrelevant values problem, we propose a new algorithm to remove irrelevant values problem of rules in the process of converting the decision tree to rules utilizing information already present in the decision tree. Our algorithm is able to handle both discrete and continuous values.
    Relation: Journal of Applied Science and Engineering 15(1), pp.89-96
    DOI: 10.6180/jase.2012.15.1.10
    Appears in Collections:[企業管理學系暨研究所] 期刊論文
    [資訊工程學系暨研究所] 期刊論文

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