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  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 生醫電子與資訊學研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/16485
完整後設資料紀錄
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dc.contributor.advisor賴飛羆(Fei-pei Lai)
dc.contributor.authorChing-Wei Hsuen
dc.contributor.author許景崴zh_TW
dc.date.accessioned2021-06-07T18:17:04Z-
dc.date.copyright2012-03-19
dc.date.issued2012
dc.date.submitted2012-02-13
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[14] P.-H. Chen, Y.-C. Lin, H.-P. Tu, S.-L. Chiang, A. M.-S. Ko, C.-L. Hsu, Y.-F. Chang, and Y.-C. Ko, 'Important prognostic factors for the long-term survival of subjects with primary liver cancer in Taiwan: A hyperendemic area,' European Journal of Cancer, vol. 43, pp. 1076-1084, 2007.
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[18] H. Cao, G. B. Melton, M. Markatou, and G. Hripcsak, 'Use abstracted patient-specific features to assist an information-theoretic measurement to assess similarity between medical cases,' J. of Biomedical Informatics, vol. 41, pp. 882-888, 2008.
[19] K. M. Gupta, D. W. Aha, and N. Sandhu, 'Exploiting Taxonomic and Causal Relations in Conversational Case Retrieval,' presented at the Proceedings of the 6th European Conference on Advances in Case-Based Reasoning, 2002.
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/16485-
dc.description.abstract臨床資料 (clinical data) 含有許多有用的醫療相關資訊,如果能夠分享其中蘊含的資訊,無論是對於病患或是醫師都會有所助益。但是臨床資會隨著病人回診檢驗,而有所增加或改變,因此可能會有多重測量 (multiple measurements) 而造成難以分析病人全部臨床資料的問題。此研究基於案例式推理 (case-based reasoning, CBR) 架構,提出多重測量案例式推理法 (multiple measurements case-based reasoning, MMsCBR),可在多重測量的情況下,尋找相似的病患,最後將結果以統計圖表呈現。此研究可提供檢索相似病患的服務給其他有需要的使用者,例如病患或是醫療人員以供參考。zh_TW
dc.description.abstractMuch valuable medical information is contained in clinical data, and it is helpful to share medical information in the clinical data. Moreover, with the subsequent consultations of patients, volumes of clinical data are growing and values of biochemistry laboratory items are multiple measured. These multiple measurements clinical data may become another problem when analyzing. This study proposes a practicable model to properly share medical knowledge and appropriately handle the multiple measurements problem. Based on case-based reasoning (CBR) model, we analyze clinical data and then the embedded multiple measurements algorithm can be used to find similar patients in the multiple measurements condition. Finally, the clinical information will be represented by the statistics approaches. The system can be used for users, such as physicians, researchers or patients. They can access the services to retrieve similar cases for references.en
dc.description.provenanceMade available in DSpace on 2021-06-07T18:17:04Z (GMT). No. of bitstreams: 1
ntu-101-R98945051-1.pdf: 731608 bytes, checksum: 79d66107e9bf96aff86f97e613c68d8a (MD5)
Previous issue date: 2012
en
dc.description.tableofcontents誌謝 i
中文摘要 ii
ABSTRACT iii
CONTENTS iv
LIST OF FIGURES vi
LIST OF TABLES vii
Chapter 1 Introduction 8
1.1 Sharing clinical data 8
1.2 The benefits of finding similar patients 8
1.3 The characteristic of clinical data 8
1.4 The method for finding similar patients 9
1.5 How to handle multiple measurements data in case-based reasoning (CBR) approach 10
1.6 The method for sharing the clinical information 10
1.7 Current study - main results and values of this study 11
Chapter 2 Background Knowledge and Related Works 12
2.1 Case-based reasoning 12
2.2 Case-based reasoning in the medical domain 13
2.3 Liver cancer related studies 14
Chapter 3 Data Source and Methodology 16
3.1 Data source 16
3.1.1 The difference between clinical data and clinical information 16
3.1.2 The introduction of cases 16
3.1.3 The introduction of the case base 18
3.2 Cross-validation 19
3.3 Feature selection methods 21
3.4 Basic case-based reasoning (BasicCBR) 22
3.5 Multiple measurements case-based reasoning (MMsCBR) 23
3.5.1 The pair weight (PW) and case weight (CW) methods of multiple measurements case-based reasoning (MMsCBR) 24
3.6 SingleCBR+MMsCBR 27
3.7 Sharing clinical information 28
3.8 Evaluation method 29
Chapter 4 Result and Discussion 31
4.1 Result 31
4.1.1 Sharing information 33
4.2 Discussion 35
Chapter 5 Conclusions and Future Work 37
5.1 Conclusions 37
5.2 Future work 37
Reference 39
dc.language.isoen
dc.subject多重測量zh_TW
dc.subject臨床資料zh_TW
dc.subject資訊分享zh_TW
dc.subject案例式推理zh_TW
dc.subjectclinical dataen
dc.subjectinformation sharingen
dc.subjectcase-based reasoning (CBR)en
dc.subjectmultiple measurementsen
dc.title以多重測量案例式推理法建構之知識分享平台: 以肝癌為例zh_TW
dc.titleThe knowledge sharable platform using multiple measurements case-based reasoning method: a case study focus on liver canceren
dc.typeThesis
dc.date.schoolyear100-1
dc.description.degree碩士
dc.contributor.oralexamcommittee李鴻璋(Hung-Chang Lee),尚榮基,莊仁輝(Jen-Hui Chuang),譚慶鼎(Ching-Ting Tan)
dc.subject.keyword臨床資料,資訊分享,案例式推理,多重測量,zh_TW
dc.subject.keywordclinical data,information sharing,case-based reasoning (CBR),multiple measurements,en
dc.relation.page43
dc.rights.note未授權
dc.date.accepted2012-02-13
dc.contributor.author-college電機資訊學院zh_TW
dc.contributor.author-dept生醫電子與資訊學研究所zh_TW
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