§ 瀏覽學位論文書目資料
  
系統識別號 U0002-1708201123171500
DOI 10.6846/TKU.2011.00608
論文名稱(中文) 關聯式法則在主動脈瘤臨床病症上的應用 以主動脈內人工血管支架置放手術為例
論文名稱(英文) Clinical Application of Association Rules for Endovascular Repair with Aortic Aneurysm
第三語言論文名稱
校院名稱 淡江大學
系所名稱(中文) 資訊工程學系碩士班
系所名稱(英文) Department of Computer Science and Information Engineering
外國學位學校名稱
外國學位學院名稱
外國學位研究所名稱
學年度 99
學期 2
出版年 100
研究生(中文) 余博淵
研究生(英文) Po-Yuan Yu
學號 698410064
學位類別 碩士
語言別 繁體中文
第二語言別 英文
口試日期 2011-07-20
論文頁數 77頁
口試委員 指導教授 - 葛煥昭
委員 - 葛煥昭
委員 - 蕭瑞祥
委員 - 施俊哲
關鍵字(中) 主動脈瘤
主動脈內人工血管支架放置術
覆膜支架
資料探勘
關聯式法則
關鍵字(英) Aortic aneurysm
Endovascular repair
Endograft
Data mining
Association rules
第三語言關鍵字
學科別分類
中文摘要
本研究在主動脈瘤臨床病症上,利用資料探勘中的關聯式法則,分析主動脈瘤內人工血管支架置放手術在不同病患中,使用不同種類覆膜支架的影響。每位病患的病史不同會影響手術的結果,而所使用的覆膜支架又會因種類不同而在主支架與覆膜有相異的材質,還有在相異支架中,所附載的藥物也會相異,這些不同的因子都會影響到手術最後的結果;然而,臨床醫師在術前檢測病患資料時,往往都是利用自己本身的經驗法則去作出治療的判斷,判斷出病患適合使用哪種覆膜支架進行手術,所以本研究目的是利用關聯式法則分析出隱藏於病患資料中,臨床醫生未發現隱藏因子,找出不同的病患最適合使用的覆膜支架,以提高手術的成功機率,更進一步分析資料找出非必要之醫療檢測項目而減少醫療資源的浪費與病患的痛苦和負擔。
英文摘要
In this study, we will use association rule of data mining to analyze the different patients with endovascular aortic repair. Using different kind of endo-graft would cause different results of surgery on people who has different patient history. The different kinds of stents and graft which compose different kinds of materials and different kinds of drug-eluting would also affect on the final result of surgery. However, the clinician almost uses his experiences to diagnose treatment which kind of stent-graft is appropriated for the patient before surgery. So, we use data mining of association rule to analyze the patient`s data and find out hidden factors which isn`t attention for clinicians. Finally, if we could find out the endograft which is appropriate for the patient, the rate of successes of the operation would increase. Moreover, we could delete some detections which are unnecessary for decreasing to waste resource of medical and burden of patient.
第三語言摘要
論文目次
第一章 緒論......1
1.1 研究背景......1
1.2 研究動機與目的......	2
1.3 論文架構......3
第二章 文獻探討......4
2.1 主動脈瘤簡介......4
2.2 主動脈瘤治療方法......7
2.2.1 傳統剖腹手術......7
2.2.2 主動脈內人工血管支架置放手術......8
2.3 支架介紹......10
2.3.1 早期的支架分類......10
2.3.2 覆膜支架......12
2.3.3 藥物塗層支架(Drug-eluting Stent)......13
2.3.4 目前上市的主動脈血管支架......14
2.4 資料探勘(Data Mining)......16
2.4.1 分類(Classification)......17
2.4.2 叢集(Clustering)......20
2.5 關聯式法則......22
2.5.1 Apriori演算法......23
2.5.2 Apriori演算法的改進......26
第三章 研究方法......31
3.1 研究流程......33
3.2 分析資料準備......38
第四章 實作分析......41
4.1 基本分析結果......42
4.2 WBC與Platelet關聯分析......45
4.3 WBC與FDP關聯分析......47
4.4 FDP與Platelet關聯分析......48
4.5 WBC + FDP + Platelet關聯分析......50
4.6 特殊規則分析......54
第五章 結論與未來研究方向......57
5.1 結論......57
5.2 未來研究方向......60
參考文獻......61
附錄-英文論文......67

圖目錄
圖2-1 主動脈區分圖......4
圖2-2 剝離型主動脈瘤分類法......6
圖2-3 傳統剖腹手術......7
圖2-4 人工血管支架放置流程圖......9
圖2-5 腹主動脈支架導管置入後......9
圖2-6 鎳鈦合金線圈型支架......10
圖2-7 Wright Z字形不繡鋼支架......11
圖2-8 Maass雙線圈型支架......11
圖2-9 氣球擴張型不繡鋼Palmaz支架......11
圖2-10 Excluder覆膜支架......12
圖2-11 Apriori演算法範例......25
圖3-1 研究流程圖......32
圖3-2 原始資料(具有不正確、遺漏、錯誤和空值)......34
圖3-3 資料轉換,將連續資料轉換成非連續性資料供關聯式法則演算法運算......35
圖3-4 資料探勘工具(IBM Intelligent Miner)......37
圖4-1 個別規則分析圖......43
圖4-2 WBC + Platelet關聯分析圖......46
圖4-3 WBC + FDP關聯分析圖......48
圖4-4 FDP + Platelet關聯分析圖......50
圖4-5 WBC + FDP +Platelet 關聯分析圖......53
圖4-6 特殊關聯分析圖......56

表目錄
表2-1 塗藥支架血管一覽表......14
表2-2 主動脈支架血管......15
表2-3 Hash Table......28
表3-1 欄位說明......38
表4-1 重要欄位表......41
表5-1 關聯法則分析結論......57
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