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題名:疾病診斷異常之偵測:關聯規則之應用
書刊名:輔仁管理評論
作者:陳垂呈
作者(外文):Chen, Chui-cheng
出版日期:2010
卷期:17:1
頁次:頁121-141
主題關鍵詞:資料探勘關聯規則疾病症狀異常診斷Data miningAssociation ruleDiseaseSymptomCareless diagnosis
原始連結:連回原系統網址new window
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  • 被引用次數被引用次數:期刊(1) 博士論文(1) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:1
  • 共同引用共同引用:0
  • 點閱點閱:170
本研究以診斷資料爲探勘的資料來源、及以某一病患爲探勘的目標,利用資料探勘的關聯規則分別從以下兩方面偵測病患的疾病診斷是否異常:一是設計一個快速探勘關聯規則的方法,並且關聯規則的前置項目組必須包含於此病患症狀中,根據關聯規則所顯示出的傾向特徵,可判斷此病患是否具有疾病診斷異常的傾向;二是設計一個快速探勘關聯規則的方法,並且關聯規則的前置項目組必須包含於此病患的診斷疾病中,根據關聯規則所顯示出的傾向特徵,可判斷此病患是否具有症狀問診異常的傾向。依據文中所提出之方法,我們設計與建置一個偵測疾病異常診斷的探勘系統。此探勘結果,對臨床經驗不足之醫療人員可以對其避免診斷的疏忽,可以提供非常有用的參考資訊。
This paper uses diagnostic data as the source of mining. We let a patient to be as the target of mining, and use association rules of data mining to detect careless diagnosis of the patient's diseases from two aspects: one is to propose a fast method to mine association rules whose antecedents are contained in the patient's symptoms, and we detect whether the diseases diagnosed is carelessness or not according to the characteristics of the association rules; the other one is to propose a fast method to mine association rules whose antecedents are contained in the patient's diseases diagnosed, and we detect whether the symptoms inquired is carelessness or not according to the characteristics of the association rules. A mining system is designed and constructed to detect careless diagnoses of diseases based on the both methods. The results of detecting can provide very useful information to avoid careless diagnoses of diseases for inexperience hospital staffs.
期刊論文
1.Tsay, Yuh-Jiuan、Chiang, Jiunn-Yann(2005)。CBAR: An Efficient Method for Mining Association Rules。Knowledge-Based Systems,18(2/3),99-105。  new window
2.Han, J.、Pei, J.、Yin, Y.、Mao, R.(2004)。Mining frequent patterns without candidate generation: a frequent pattern tree approach。Data Mining and Knowledge Discovery,8(1),53-87。  new window
3.Park, Jong-Soo、Chen, Ming-Syan、Yu, Philips S.(1997)。Using a hash-based method with transaction trimming for mining association rules。IEEE Transactions on Knowledge and Data Engineering,9(5),813-825。  new window
4.Agarwal, R. C.、Aggarwal, C. C.、Prasad, V. V. V.(2001)。A tree projection algorithm for generation of frequent itemsets。Journal of Parallel and Distributed Computing,61(3),350-371。  new window
5.Chen, Ming-Syan、Han, Jiawei、Yu, Philip S.(1996)。Data Mining: An Overview from a Database Perspective。IEEE Transactions on Knowledge and Data Engineering,8(6),866-883。  new window
會議論文
1.Ye, Xinfeng、Keane, John A.(1997)。Mining association rules with composite items。IEEE International Conference on Computational Cybernetics and Simulation,(會議日期: 12-15 Oct. 1997),1367-1372。  new window
2.Agrawal, R.、Imielinski, T.、Swami, A.(1993)。Mining Association Rules between Sets of Items in Very Large Database。The ACM SIGMOD Conference on Management of Data,207-216。  new window
3.Agrawal, R.、Srikant, R.(1994)。Fast algorithms for mining association rules in large database。The 20th International Conference on Very Large Data Bases。Morgan Kaufmann Publishers Inc.。478-499。  new window
圖書
1.Han, Jiawei、Kamber, Micheline(2006)。Data Mining: Concepts and Techniques。San Francisco:Morgan Kaufmann Publishers。  new window
其他
1.朱彩屏(2004)。資料探勘在醫療資料庫之研究--以疝氣臨床路徑為例。  延伸查詢new window
2.吳素英(2004)。資料探勘技術應用於知識管理系統之建構--以醫院疾病分類管理為例。  延伸查詢new window
3.吳國禎(1999)。資料探索在醫學資料庫之應用。  延伸查詢new window
4.唐壽生(2004)。資料探勘技術應用於肺結核病患完治的預測。  延伸查詢new window
5.陳世源(2000)。資料採礦技術在病例與藥品關連性之研究。  延伸查詢new window
6.陳迪祥(2003)。以資料探勘技術發掘疾病隱藏關係之研究。  延伸查詢new window
7.俞旭昇(2002)。以資料探勘技術發掘疾病隱藏關係之研究。  延伸查詢new window
8.黃勝崇(2001)。資料探勘應用於醫療院所輔助病患看診指引之研究。  延伸查詢new window
9.潘雅雪(2007)。資料探勘技術於疾病診斷之應用。  延伸查詢new window
10.Coenen, F. ; Leng, P. & Ahmed, S.(2004)。Data Structure for Association Rule Mining T-trees and P-trees。  new window
11.Da Silva Camargo, S. ; Martins Engel, P.(2002)。MiRABIT: A New Algorithm for Mining Association Rules。  new window
12.Holt, J. D. ; Chung, S. M.(2002)。Mining Association Rules Using Inverted Hashing and Pruning。  new window
13.Li, Z. C. ; He, P. L. & Lei, M.(2005)。A High Efficient AprioriTid Algorithm for Mining Association Rule。  new window
14.Lin, Z. K. ; Yi, W. G. ; Lu, M. Y. ; Liu, Z. & Xu, H.(2009)。Correlation Research of Association Rules and Application in the Data about Coronary Heart Disease。  new window
15.Liu, P. Q. ; Li, Z. Z. & Zhao, Y. L.(2004)。Effective Algorithm of Mining Frequent Itemsets for Association Rules。  new window
16.Palaniappan, S. & Awang, R.(2008)。Intelligent Heart Disease Prediction System Using Data Mining Techniques。  new window
17.Tsipouras, M. G. ; Exarchos, T. P. ; Fotiadis, D. I. ; Kotsia, A. P. ; Vakalis, K. V. ; Naka, K. K. ; Michalis, L. K.(2008)。Automated Diagnosis of Coronary Artery Disease Based on Data Mining and Fuzzy Modeling。  new window
18.Tsay, Y. J. & Chang-Chien, Y. W.(2004)。An Efficient Cluster and Decomposition Algorithm for Mining Association Rules。  new window
 
 
 
 
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