臺灣博碩士論文加值系統

動機：自民國71年以來我國十大死因排名第一名即為惡性腫瘤，糖尿病和惡性腫瘤在歷年來均出現在國人十大死因排行之中，對於國人的健康具有重大的影響，以致醫療資源的耗用甚鉅。且根據行政院衛生福利部的2012年統計資料顯示，肝癌是台灣癌症死亡的第二大原因，每年約有7,000名病患死於肝癌。主要的原因是B型肝炎及C型肝炎的高盛行率，使慢性肝病得以進一步發展成肝硬化及肝癌。目的：利用類神經網路建構第二型糖尿病確診後罹患為肝癌之預測模型。方法：藉由全民健康保險研究資料庫找出第二型糖尿病罹患為肝癌之研究對象，並利用類神經網路建構預測模型，預測模型所使用之因素則利用卡方檢定來了解其因素與肝癌之間關聯分析之檢定結果。研究結果：研究樣本共65,871人，其中共有515人得到癌症；男性共31947人，其中358得到癌症；女性共33924人，其中157人得到癌症。而疾病風險預測模型方面，類神經網路所建立出之模型其Sensitivity可達0.802、Specificity可達0.773、ROC取線下之面積可達0.873。結論：酒精性預測因子所建立出的預測模型準確性均較為低落，其原因可能為糖尿病與酒精性肝臟疾病因子間很有關聯且酒精性肝臟疾病因子與肝癌也很有關係，但糖尿病卻無直接與肝癌間有直接影響所以導致酒精性肝臟疾病因子進行預測較為低落，在未來的研究應結合更多不同的資料庫，如個人生活習慣資料庫與健康檢查資料庫，進而再尋找可能引發糖尿病確診後罹患為肝癌之風險因子。

Background: Since 1982 the first one causes of death is cancer. And diabetes is also the top 10 of death in Taiwan, it severely impact people`s health, and cause a lot medical resources in Taiwan. And according to statistics in 2012 by Ministry of Health and Welfare (Taiwan) show that liver cancer is the second leading cause of cancer death in Taiwan, about 7,000 patients died of liver cancer. The main reason is the high prevalence of hepatitis B and hepatitis C, lead chronic liver disease develops into liver cancer. Objective: Using neural networks to construct a predict model that Type 2 diabetes after diagnosed conversion to Liver cancer. Methods: By Using National Health Insurance Research Database to identify Liver cancer complicated by diabetes and use of neural network to construct prediction model. Predictive models factors is use of the chi-square test and T test to test the relation between factors and Lever cancer. Results: In this study we include 31,953 males, and 364 people have liver cancer; include 33,767 females, and 157 have liver cancer; totally include 65,356 people, and 521 people have cancer. The disease risk prediction models, was created by neural network, Sensitivity is 0.802, Specificity is 0.773, and Area Under ROC is 0.873. Conclusion: The model create by Alcohol factor are lower accuracy, the reason maybe is that diabetes and Alcoholic liver disease have relation, and alcohol-related factor have relation with Liver cancer, but dabetes didn’t has a direct impact to liver cancer, so cause that alcohol-related factor can’t to predict liver cancer, In future we should be combined with other database, such as personal health database and health record database, which can find more risk factors.

誌謝 ii
目錄 iii
圖目錄 vi
表目錄 vii
論 文 摘 要 viii
Abstract x
第一章 緒論 1
1.1 前言 1
1.2 研究動機 1
1.3 研究目的 2
第二章 文獻探討 3
2.1 糖尿病 3
2.1.1 第1型糖尿病 3
2.1.2 第二型糖尿病 4
2.1.3 糖尿病的併發症 5
2.2 肝臟的構造與生理功能 9
2.3 慢性肝炎 10
2.3.1 病毒型慢性肝炎 10
2.3.2 非病毒型慢性肝炎 11
2.4 肝硬化 12
2.5 肝癌 13
2.6 糖尿病與肝癌 14
2.7 類神經網路應用於醫學上 16
第三章 研究方法 17
3.1 研究架構 17
3.2 資料來源與研究對象 18
3.2.1 資料來源 18
3.2.2研究對象 24
3.3 預測模型使用架構 26
3.4 預測因素建立 26
3.5設定不同預測模組 27
3.6 預測模型建立工具與交叉驗證 28
3.6.1 類神經網路 28
3.6.2 邏輯斯迴歸分析 29
3.7 應用預測模型建立系統 30
第四章 研究結果 31
4.1 糖尿病與各十大癌症供並關聯分析 31
4.2 研究樣本 32
4.3 因素分析 34
4.4 預測模型結果比較 35
4.4.1 第一階段預測模型 35
4.4.2 第二階段預測模型結果比較 39
4.5 預測表現比較總結 43
4.6 糖尿病確診後罹患為肝癌之預測系統 46
第五章 結論與討論 48
參考文獻 51

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