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系統識別號 U0026-0109201111150000
論文名稱(中文) 非酒精性脂肪肝之預測模型
論文名稱(英文) A Predictive Model for Nonalcoholic Fatty Liver Disease
校院名稱 成功大學
系所名稱(中) 工程科學系專班
系所名稱(英) Department of Engineering Science (on the job class)
學年度 99
學期 2
出版年 100
研究生(中文) 郭瑞祥
研究生(英文) Rui-Xiang Guo
學號 n97981053
學位類別 碩士
語文別 英文
論文頁數 55頁
口試委員 指導教授-侯廷偉
口試委員-吳晉祥
口試委員-楊宜青
口試委員-鄧維光
口試委員-陳澤生
中文關鍵字 非酒精性脂肪肝  資料採礦  模糊理論 
英文關鍵字 nonalcoholic fatty liver disease (NAFLD)  data mining  fuzzy 
學科別分類
中文摘要 非酒精性脂肪肝是越來越盛行的現代文明病,而且有年輕化的趨勢,如果未加以適當控制,將會進一步損害患者的健康。早期發現並且早期治療,可以大幅降低醫療成本。本研究使用成大醫院家庭醫學部所蒐集的資料,針對非酒精性脂肪肝提出一個預測模型。首先運用資料採礦的技術,探索出非酒精性脂肪肝與各種症狀的關聯性。在建立明確的規則後,再導入模糊理論的方法以及對於資料集的調整,對模型做進一步的改善。所提出的模型具有89.06%的特異性(specificity),而對輕度與中度以上脂肪肝的敏感性(sensitivity)分別是70.07%和57.19%。
英文摘要 Nonalcoholic fatty liver disease (NAFLD) is a common lifestyle disease. NAFLD victims are getting younger and younger and NAFLD can endanger people's health if not controlled properly. Early detection and treatment of NAFLD patients can lower the medical cost significantly. This study uses the data from the Department of Family Medicine of National Cheng Kung University Hospital to propose a predictive model for NAFLD. This model depends on the data mining techniques which are used to discover the various symptom associations with NAFLD. After a crisp rule of NAFLD is created, the fuzzy theory and adjustment of dataset are introduced to improve the model. The specificity of the proposed model is 89.06% and the sensitivities of mild and moderate (and above) NAFLD are 70.07% and 57.19% respectively.
論文目次 Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Purpose 2
1.3 Thesis organization 3
Chapter 2 Literature review 5
2.1 Nonalcoholic fatty liver disease 5
2.2 Data mining techniques 11
2.3 Fuzzy theory 21
Chapter 3 Study method 30
3.1 Dataset 30
3.2 Tool 32
3.3 Methods 33
Chapter 4 Results and Validation 38
4.1 Results 38
4.2 Validation 43
Chapter 5 Conclusion and Future Work 48
5.1 Conclusion 48
5.2 Future work 49
References 51
Appendix 54
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