成功大學博碩士論文系統

簡易檢索 / 詳目顯示

回結果列表

研究生：	林敏雄 Lin, Min-hsiung
論文名稱：	正規化概念分析方法應用於疾病分類的知識探索及預測 Formal concept analysis applied in international classification of disease, knowledge discovery and prediction
指導教授：	李昇暾 Li, Sheng-tun
學位類別：	碩士 Master
系所名稱：	管理學院 - 工業與資訊管理學系碩士在職專班 Department of Industrial and Information Management (on the job class)
論文出版年：	2007
畢業學年度：	95
語文別：	中文
論文頁數：	58
中文關鍵詞：	模糊正規概念分析、疾病分類、自然語言處理、知識管理
外文關鍵詞：	classification of disease, knowledge management, natural language processing, fuzzy formal concept analysis
相關次數：	點閱：104 下載：9
分享至:	分享至facebook 分享至twitter

查詢本校圖書館目錄查詢臺灣博碩士論文知識加值系統勘誤回報

健保局為了解決醫療財務的沈重壓力，控制不斷上漲的醫療費用，擬於民國97 年起，分 4 年導入診斷關係群(Diagnosis Related Group, DRG)包裹給付制度，DRG 的編碼是根據ICD-9-CM 碼(International Classification of Diseases,Ninth Revision, Clinical Modification)來編碼，若病歷資料不完整、疾病分類人員編碼不正確，都可能影響醫院的財務收入，所以提昇疾病分類人員的編碼品質變的極為迫切且重要。希望藉由本研究萃取出隱含在出院病歷摘要編碼訊息來解決所面臨的新問題，期望以知識外顯化來協助疾病分類人員編碼。
本研究以模糊正規概念分析(FFCA)及自然語言處理(NLP)萃取出院病歷摘要內容，以圖形化的方式呈現疾病分類關鍵字詞的概念與關係，並提供疾病分類隱性知識的探索，強化整個疾病分類知識的架構、預測病歷可能編碼，藉以提升疾病分類人員編碼效率、增加正確性。

To solve the financial burden and incontrollable medical treatment fee,the Bureau of National Health Insurance decided to function (Diagnosis Related Group, DRG) within 4 year from this 2007, Reimbursement System. DRG is fundationed on ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification), however, this is going to be affect the profits of each hospital because of the incomplete information or the coding quality of coding specialist classification of disease. So improving the coding quality of specialists is an important.Hopefully, the study is helpful for finding the recessive message to decode the new coming problems. Furthermore, to assist the coding specialist for being better coding.
This study explores the knowledge discovery from the discharge summery via the FFCA and NLP. It provides the exploration of the recessive message, enforcement of the classification of disease framework and prediction of possible coding to show the keywords between the concept and relationship.

目錄................................................................I
圖目錄............................................................III
表目錄.............................................................IV
第一章 緒論.........................................................1
1.1 研究背景....................................................1
1.2 研究動機....................................................2
1.3 研究目的....................................................2
1.4 研究範圍....................................................3
1.5 論文架構....................................................3
第二章 文獻探討.....................................................4
2.1 疾病分類....................................................4
2.1.1 目前我國疾病分類制度概況..............................4
2.1.2 疾病分類的基本步驟....................................5
2.1.3 疾病分類在知識管理的應用現況..........................6
2.2 醫學圖書館標題表............................................8
2.3 知識探索...................................................10
2.3.1 資料探勘.............................................11
2.3.2 資訊擷取.............................................12
2.4 正規概念分析...............................................17
2.4.1 正規化概念分析定義與原理.............................17
2.4.2 正規化概念分析法.....................................20
第三章 研究方法....................................................23
3.1 研究架構...................................................23
3.2 自然語言處理程序...........................................25
3.3 資訊檢索...................................................28
3.4 模糊正規概念分析...........................................30
第四章 實作與分析..................................................33
4.1 系統架構...................................................33
4.1.1 系統環境.............................................33
4.1.2 資料來源.............................................35
4.1.3 資料處理.............................................37
4.2 實作目的...................................................38
4.3 實作結果...................................................38
4.3.1 概念屬性及規則.......................................38
4.3.2 編碼預測.............................................42
4.4 實驗評估...................................................47
第五章 討論與結論..................................................50
5.1 研究結論...................................................50
5.2 研究討論...................................................51
5.3 未來展望...................................................54
參考文獻...........................................................55

圖目錄
========================================
圖2-1 Concept Explorer1.3 屬性概念圖..............................20
圖2-2 概念圖產生屬性Association Rules.............................21
圖2-3 案例物件及屬性概念圖........................................21
圖3-1 系統架構圖..................................................24
圖3-2 GATE 系統畫面................................................26
圖3-3 GATE 斷詞畫面................................................28
圖4-1 Concept Explorer1.3 概念畫面.................................34
圖4-2 ConceptExplorer 產生概念規則界面.............................34
圖4-3 ConceptExplorer 產生模糊概念方格界面.........................35
圖4-4 出院病歷摘要格式............................................36
圖4-5 出院病歷摘要訓練樣本分佈情況................................36
圖4-6 本研究FCA 概念規則圖........................................39
圖4-7 本研究FCA 概念規則圖........................................39
圖4-8 實驗一FCA 概念規則圖........................................40
圖4-9 實驗一FCA 屬性概念中文說明..................................40
圖4-10 訓練物件分佈圖.............................................42
圖4-11 相同診斷代碼病歷文件集中圖示...............................43
圖4-12 存放於詞組資料庫...........................................43
圖4-13 實驗二測試文件落點概念圖...................................44
圖4_14 實驗三的完整概念方格........................................45
圖4-15 實驗三 編碼指引概念圖......................................46
圖4-16 實驗三 分群預測概念圖......................................46
圖4-17 本研究測試樣本的分佈.......................................47
圖4-18 測試樣本各代碼預測成功分佈情況.............................48
圖4-19 本研究各項評估數據.........................................48

表目錄
========================================
表2-1 醫療或疾病分類在知識管理領域中的相關研究整理.................7
表2-2 資訊檢索在醫療上相關研究及應用理............................15
表2-3 各專家學者對FCA 所下的定義..................................19
表4-1 系統架構.....................................................33
表4-2 詞組數的改變................................................37
                                    

余金燕，潘德樑疾病分類實務。台北市：合記圖書出版社，(2003)。
范碧玉病歷管理理論與實務，台灣病歷管理協會，(2003)。
范慧蘭以本體論建構疾病分類知識庫系統。國立高雄第一科技大學，資訊管理研究所碩士論文 (2005)
陳振亨應用類神經網路於心血管疾病分類與診斷。東海大學工業工程與經營資訊學系碩士論文 (2004)。
楊正銘以文字探勘技術應用於疾病分類之輔助系統-以出入院病歷摘要為例。臺北醫學大學醫學資訊研究所碩士論文 (2003)。

Abasolo JM, Gmez M. MELISA An Ontology-based Agent for Information Retrieval in Medicine. Proc of ECDL 2000 Workshop on the Semantic Web, Lisbon, Portugal. Session 3; 21. (2000)
Agichtein, E., Lawrence, S. and Gravano, L., Learning search engine specific query transformations for question answering Proceedings of the 10th World Wide Web Conference,pp. 169-178. ( 2001)
Baeza-Yates R and Ribeiro-Neto B. Modern Information Retrieval. ACM Press, New York. (1999).
Carpineto, C. and Romano, G. Exploiting the Potential of Concept Lattices for Information Retrieval with CREDO. Journal of Universal Computing, Vol. 10, No. 8, pp.985-1013.(2004)
Carpineto, C and Romano, G. Information retrieval through hybrid navigation of lattice representations. International Journal of Human-Computer Studies Volume: 45, Issue: 5, November, 1996, pp. 553-578 (2006)
Formica, A. Ontology-based concept similarity in Formal Concept Analysis. Information Sciences, Vol. 176, No. 18, pp.2624-2641. (2006)
Ganter, B. and Wille, R. Implikationen und Abhangigkeiten zwischen Merkmalen. in: P. O.Degens, H.-J. Hermes, and O. Opitz(Eds.), Die Klassifikation und ihr Umfeld. Frankfurt:Indeks, pp.171-185. (1986)
Gary H. Merrill, The Babylon Project: Toward an Extensible Text-Mining Platform, IT Pro,IEEE Computer Society, March | April. (2003)
Glenisson P, Antal P, Mathys J, MoreauY, De Moor B. Evaluation of the Vector Space Representation in Text-based Gene Clustering. Pacific Symposium on Biocomputing.pp.391–402. (2003)
Homayouni R, Heinrich K, Wei L, Berry MW. Gene Clustering by Latent Semantic Indexing of MEDLINE Abstracts. Bioinformatics. pp.21(1):104-15. (2005)
Ikeji, A. and Fotouhi, F. An adaptive real-time web search engine. Proceedings of the Second International Workshop on Web Information and Data Management ,pp.12-16.( 1999)
Jiang, G., Ogasawara, K., Endoh, A., and Sakurai, T. Context-based ontology building support in clinical domains using formal concept analysis. International Journal of Medical Informatics, Vol. 71, No. 1, pp.71-81. (2003)
Mao W, Chu WW. Free-text Medical Document Retrieval via Phrase-based Vector SpaceModel. Proceedings of AMIA Symposium. pp.489-93. (2002)
Moreda P, Navarro B, Palomar M. Corpus-based semantic role approach in information retrieval. Data & Knowledge Engineering, Vol. 61, Issue: 3, June, 2007, pp.467-483.(2006)
Ono H, Takabayashi K, Suzuki T, Yokoi H, Imiya A, Satomura Y. Extraction of Diagnosis Related Terminological Information from Discharge Summary. Medinfo. (2004)
Richard J. , Michael W. Data Mining A Tutorial-Based Primer. Addison-Wesley. (2003)
Surdeanu, M, Moldovan, D. and Harabagin, S. Performance Analysis of a Distributed Question/Answering System, Proceedings, 15th International Conference on Parallel and Distributed Processing Symposium, pp. 23-27. (2001)
Tho, Q.T., Hui, S.C., and Cao, T.H. A Fuzzy FCA Approach for Citation-based Document Retrieval. IEEE Conference on Cybernetics and Intelligent Systems (CIS), Singapore,pp.578-583. (2004)
Tho, Q.T., Hui, S.C., Fong, A.C.M., and Cao, T.H. Automatic Fuzzy Ontology Generation for Semantic Web. IEEE Transactions on Data and Knowledge Engineering, Vol. 18, No. 6, pp.842-856. (2006)
Thomas, B., , URL diving, IEEE Internet Computing, Vol. 2, pp.92-93. (1998)
Uta, P. Formal concept analysis in information science. Annual review of information science and technology, Vol. 40, pp.521-543. (2006)
Wille, R. Restructuring lattice theory: an approach based on hierarchies of concepts. in: Ivan Rival(Ed.), Ordered sets. Dordrecht-Boston: Reidel, pp.445-470. (1982)
Yevtushenko, S. A. System of data analysis "Concept Explorer". (In Russian). Proceedings of the 7th national conference on Artificial Intelligence KII-2000, pp. 127-134. (2000)
Zhou, L, Author, Reprint Author Zhou Li Zhou, Li , Tao, Y, et al. Terminology model discovery using natural language processing and visualization techniques. J BIOMED INFORM 39 (6): 626-636. (2006)

校內：2010-07-12公開
校外：2010-07-12公開

簡易檢索 / 詳目顯示

相關論文