§ 瀏覽學位論文書目資料
  
系統識別號 U0002-3006201010282700
DOI 10.6846/TKU.2010.01113
論文名稱(中文) 整合決策樹與統計分析超音波抽取注入酒精在子宮內膜異位症療效
論文名稱(英文) Statistical and Decision Tree analysis of effectiveness of ultrasound-guided aspiration of ovarian endometriomas
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 98
學期 2
出版年 99
研究生(中文) 莊斯婷
研究生(英文) Ssu-Ting Chuang
學號 697410560
學位類別 碩士
語言別 繁體中文
第二語言別 英文
口試日期 2010-06-15
論文頁數 67頁
口試委員 指導教授 - 蔣定安
委員 - 葛煥昭
委員 - 王鄭慈
委員 - 蔣定安
關鍵字(中) 資料探勘
決策樹
CART
統計t test
子宮內膜異位症
關鍵字(英) Data mining
Decision tree
CART
t test of Statistical
ovarian endometriomas
第三語言關鍵字
學科別分類
中文摘要
在醫療統計上,有許多學者證實了“超音波抽取注入酒精治療注入酒精時間在十分鐘以上至不抽出,有較佳的療效”,但是卻很少學者探討“不同狀況患者對酒精治療時間長短與復癒率之間的關係”,所以本論文以資料探勘的方式探討此問題。而決策樹演算法在規則表現以樹狀方式呈現,因此在知識的透明度上有很好的表現,且決策樹可針對目標類別同時分析類別屬性與數值屬性欄位,找出對於最佳屬性切點。但決策樹分類的結構是屬於區域的特性且有過度擬合(over-fitting)問題。故在本文中,擬利用決策樹CART演算法產生規則,將決策樹規則的節點重新組合產生所有可能的規則,再結合統計t test驗證規則的顯著,以找出未被發掘而有意義的知識。實驗結果表明,我們的做法可以找到子宮內膜異位症不同狀況患者對酒精治療時間長短與復癒率的一些新知識。
英文摘要
Although several researchers have performed statistical methods to prove that aspiration followed by injection of 95% ethanol left in situ (retention) is an effective treatment of ovarian endometriomas, very few of them discuss the different conditions that could generate different recovery rate for the patients. Therefore, this study adopts the statistical method and decision tree techniques together to analyze the postoperative status of ovarian endometriosis patients under the conditions. Since our collected data set is small, only contains 212 records, we use all of these data as the training data. Therefore, instead of using a resultant tree to generate rules directly, we use the value of each node as a cut point to generate all possible rules to the tree first. Then, using t test to verify rules to discover some useful description rules after all possible rules to the tree are generated. The experimental results show that our approach can find some new interesting knowledge about the recurrent ovarian endometriomas under the different conditions.
第三語言摘要
論文目次
第1章	緒論	1
1.1	研究動機及研究目的	2
1.2	論文架構	4
第2章	相關研究	5
2.1	資料探勘	5
2.2	決策樹演算法	9
2.2.1	決策樹演算法過程	10
2.2.2	分類回歸樹(CART,Classification and Regression Tree)	13
2.3	子宮內膜異位症	18
2.3.1	子宮內膜異位症的臨床症狀	19
2.3.2	子宮內膜異位症的檢查方式	21
2.3.3	子宮內膜異位症的分級	22
2.3.4	子宮內膜異位治療方法	23
第3章	研究方法	26
3.1	流程架構及研究方法	26
3.2	資料收集	28
3.3	基本統計	32
3.3.1	超音波抽取注入95%酒精治療	33
3.3.2	患者的基本欄位統計	34
3.3.3	復癒率計算方式	35
3.3.4	超音波抽取注入酒精治療時間長短之基本統計	35
第4章	研究結果與分析	37
4.1	實作環境說明	37
4.2	實作目標	37
4.3	決策樹結果分析	38
4.4	使用決策樹的問題與解決辦法	41
4.5	術前CA_125檢驗值的影響	43
4.6	術前CYST_SIZE測量值與BMI檢測值的影響	47
4.7	患者狀況、95%酒精注入囊腫內置留時間與術後復癒狀況關係	50
第5章	結論與未來相關研究	54
5.1	結論	54
5.2	未來相關研究	55
參考文獻	56
附錄—英文論文	58

圖目錄
圖2.1知識發掘流程圖	6
圖2.2 預測是否玩網路遊戲的決策樹	9
圖2.3 從訓練資料建構決策樹的基本演算法	11
圖3.1 研究方法流程圖	27
圖3.2 二元變異統計	30
圖3.3 CYST_SIZE的二元變異統計	30
圖3.4 OP_TOTAL_FLAG的二元變異統計	31
圖4.1 IBM的DB2 INTELLIGENT MINER FOR DATA V8.1產生決策樹結果	38
圖4.2決策樹結果	38
圖4.3 結合酒精時間與復癒欄位新目標決策樹結果	50

表目錄
表2.1 CART屬性選擇方法Gini index在電腦購買與否顧客資料庫	15
表2.2 美國生殖醫學會子宮內膜異位症的分級	22
表3.1決策樹參數欄位	32
表3.2患者的基本欄位統計	34
表3.3超音波抽取注入95%酒精治療以時間分群對復癒率統計	36
表4.1 決策樹結果規則分群與復癒率之統計檢定	40
表4.2 決策樹切點所組成的規則	42
表4.3 CA_125的t test結果	43
表4.4 CA_125 ≥146.81酒精注入時間長短復癒與否	45
表4.5 Cyst_size與BMI的t test結果	48
表4.6 酒精置入時間長短的t test結果	52
參考文獻
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