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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/96021


    Title: Generating Diagnostic Rules Directly from Experimental Data
    Authors: Su, Mu-Chun
    Contributors: 淡江大學電機工程學系
    Keywords: 診斷;實驗數據;類神經網路;模糊系統;Diagnosis;Experimental Data;Neural Network;Fuzzy System
    Date: 1996-05
    Issue Date: 2014-02-13 11:35:44 (UTC+8)
    Abstract: Traditionally, a major task in building a medical diagnosis expert system is the process of acquiring the required knowledge in the form of production rules(IF...THEN...). Alternative knowledge acquisition approach to articulating knowledge required for diagnostic tasks are presented in this paper. Each approach has its own advantages and disadvantages. The ultimate goal of these approaches is to free human experts from tedious diagnosis loads. The effectiveness of these approaches is demonstrated by an example of a hypothesis regarding the pathophysiology of diabetes.
    Relation: 第二屆國際醫學工程週論文集=Proceedings of the 2nd Medical Engineering Week of the World,頁438-443
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Proceeding

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