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題名:以資料探勘技術建立病患就醫導引--以胃腸科病患為例
書刊名:醫療資訊雜誌
作者:莊宗南龔榮源陳俊龍
作者(外文):Chuang, Tzung-nanKung, Jung-yuanCheng, Jiunn-lung
出版日期:2006
卷期:15:1
頁次:頁17-34
主題關鍵詞:醫療資訊資料探勘QDT演算法決策樹Medical informationData miningQDT algorithmDecision tree
原始連結:連回原系統網址new window
相關次數:
  • 被引用次數被引用次數:期刊(2) 博士論文(2) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:2
  • 共同引用共同引用:5
  • 點閱點閱:76
由於全民健康保險的開辦實施,提供了人民生活上的醫療保障,但不可諱言的,由於醫療資源的浪費,也造成了政府財政上極大的負擔。究其原因,除了健保體制本身的問題外,國人未能具備正確的就醫觀念也是其中一項重大的因素。由於一般民眾並未具備足夠的醫療常識,因此往往在有了某些自覺症狀時,無法判斷是何種疾病所引起,以及是否該即時就醫,因而延誤病情的治療。這不僅將增加日後治療的困難,甚至可能危及生命,同時也讓社會增加了額外的醫療成本。 資料探勘是近幾年在資料庫應用方面相當熱門的技術,並且廣泛的應用在各種領域。在本篇研究中,我們將資料探勘技術應用在醫療領域,期望能對上述問題有所改善。在探勘過程中,利用高效率之關聯規則探勘演算法(QDT)來歸納出各疾病與其可能症狀的高頻項目組,再以決策樹(Decision Tree)分類方法推論症狀與疾病兩者之間的關係,讓患者可藉由本研究的結果來瞭解其可能發生的疾病。本研究結果除了可作為一般民眾就醫時的參考資訊外,亦可提供醫師作為診斷時的參考依據,並期望能對維護全民健康有所貢獻。
The establishment of the National Health Insurance provides the medical protection for the people. However, it is also a heavy financial burden for the government because of the waste of the medical resources. There are many reasons to lead the waste of the medical resources. One of them is that most patients do not have enough medical senses. When patients have some symptoms, they cannot identify what disease they have, and they do not know which department they should consult. Therefore, they often consult a wrong doctor and delay the treatment. It causes more difficulty in curing the disease and even brings forth the death of patients. Furthermore, it increases the additional social medical resources. Data mining techniques has been successfully applied in various fields. In this paper, we use the data mining techniques to process the medical data and establish the patient guide that can help patients to identify what disease they have. We employ both association rule and classification techniques for the most part of the mining process. First, Quick Decomposition Table algorithm is utilized to induce the large item sets between symptoms and diseases. Secondly, C4.5 algorithm that is one of the most popular decision tree techniques is adopted to classify the diseases what symptoms lead to. Finally, we can establish the patient guide to let patients know which diseases they may have. The patient guide can be a guide for the patients to consult the right doctor as well as a reference for the doctor to cure diseases. Moreover, we expect this research results can be helpful to human health.
期刊論文
1.陳仕昇、陳彥良、許秉瑜(2000)。在序列式資料中挖掘序列規則。資訊管理學報,6(2),167-182。  延伸查詢new window
2.Chen, Ming-Syan、Han, Jiawei、Yu, Philips S.、Park, J. S.(1996)。Data Mining: An Overview from database Perspective。IEEE Transaction on Knowledge and Data Engineering,8(6),866-883。  new window
3.Swami, A.、Agrawal, R.、Imielinski, T.(1993)。Database mining: a performance perspective。IEEE Transactions on Knowledge and Data Engineering,5(6),914-925。  new window
4.簡禎富、吳文婷(1997)。醫療決策分析:以唐氏症之診斷為例。醫療資訊雜誌,6,39-53。new window  延伸查詢new window
5.Fayyad, U. M.、Piatetsky-Shapiro, G.、Smyth, Padhraic、The, K. D. D.(1996)。Process for Extracting Useful Knowledge from Volumes of Data。Communications of the ACM,39(11),27-33。  new window
6.Quinlan, J. R.(1986)。Induction of Decision Trees。Machine Learning,1(1),81-106。  new window
7.蔣肇慶、林熙楨(1999)。資料開採在醫療資訊的研究。醫療資訊雜誌,第九期,頁71-82。new window  延伸查詢new window
8.簡文山等(1997)。建立臺灣醫療資訊交換中心之藍圖。醫療資訊雜誌,第六期,頁54-66。  延伸查詢new window
會議論文
1.趙景明、林振群(2002)。應用資料探勘技術於資料倉儲環境之研究。「第13屆國際資訊管理學術研討會」。  延伸查詢new window
2.Agrawal, R., Imielinski, T., and Swami, A.(1993)。“Mining association rules between sets of items large database,”pp. 207-216。  new window
3.Fayyad, U.(1997)。“Data mining and knowledge discovery in databases: implications for scientific databases,”pp. 2-11。  new window
學位論文
1.吳國禎(2000)。資料探索在醫學資料庫之應用(碩士論文)。中原大學。  延伸查詢new window
2.翁龍珠(2002)。應用資料探勘於目標行銷之研究-以製藥業為例。  延伸查詢new window
3.錢依佩(2003)。高效率之關聯法則探勘演算法。  延伸查詢new window
圖書
1.Han, Jiawei、Kamber, Micheline(2000)。Data mining: Concepts and techniques。Morgan Kaufmann Publishers。  new window
2.Quinlan, J. Rose(1993)。C4.5: Programs for Machine Learning。Morgan Kaufmann Publishers。  new window
3.林傑斌、劉明德(2002)。資料採掘與OLAP的理論與實務。文魁資訊股份有限公司。  延伸查詢new window
4.林肇堂、Ronald L. Koretz Marvin Derezi(1983)。實用腸胃學。茂昌圖書有限公司。  延伸查詢new window
5.曾新穆、李建億、Richard J. Roiger Michael W. Geatz(2003)。資料探勘Data Mining -A Tutorial-Based Primer。東華書局。  延伸查詢new window
6.葉涼川、Alex Berson Stephen Smith Kurt Thearling(2002)。CRM Data Mining應用系統建置。美商麥格羅,希爾國際股份有限公司。  延伸查詢new window
7.Berry, M. J. A., and Linoff, G(1997)。“Data Mining: For Marketing, Sales, and Customer Support”,。Wiley Computer Publishing。  new window
8.Fayyad, U. M., Shapiro, G. P., Smyth, P.,(1996)。“From Data Mining to Knowledge Discovery: An Overview,”。Advances in Knowledge Discovery and Data Mining。  new window
9.IBM(199)。“IBM Intelligent Miner For Data”。IBM。  new window
10.Inmon, W. H(199)。“Building The Data Warehouse”,。John Wiley & Sons。  new window
11.Stuart Russell, Peter Norving(1995)。“Artifical Intelligence: A Modern Approach”。Prentice-Hall。  new window
12.Thomas M. Connolly, Carolyn E. Begg(1998)。“Database System: A practical approach to design implementation and management”。Addison-Wesley。  new window
13.William Silen(2000)。“Cope’s Early Diagnosis of the Acute Abdomen”。Oxford University Press。  new window
 
 
 
 
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