English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 45172/58348 (77%)
造訪人次 : 2471832      線上人數 : 185
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://libir.tmu.edu.tw/handle/987654321/53946


    題名: 以健保資料庫與癌症登記檔建構糖尿病確診後罹患為肝癌之預測模型
    Using NHIRDB and Taiwan Cancer Registry to Construct a Predict Model for Diagnosed Type 2 Diabetes and Liver Cancer.
    作者: 林宥安
    Lin, Yu-An
    貢獻者: 醫學資訊研究所
    徐建業
    關鍵詞: 全民健康保險研究資料庫;糖尿病;肝癌;類神經網路;預測模型
    National Health Insurance Research Database;Diabetes;Liver;Neural Networks;Predictive Models
    日期: 2014-06-19
    上傳時間: 2018-11-15 12:12:16 (UTC+8)
    摘要: 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.
    描述: 碩士
    指導教授-徐建業
    委員-劉立
    委員-邱泓文
    資料類型: thesis
    顯示於類別:[醫學資訊研究所] 博碩士論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    index.html0KbHTML147檢視/開啟


    在TMUIR中所有的資料項目都受到原著作權保護.

    TAIR相關文章

    著作權聲明 Copyright Notice
    • 本平台之數位內容為臺北醫學大學所收錄之機構典藏,包含體系內各式學術著作及學術產出。秉持開放取用的精神,提供使用者進行資料檢索、下載與取用,惟仍請適度、合理地於合法範圍內使用本平台之內容,以尊重著作權人之權益。商業上之利用,請先取得著作權人之授權。

      The digital content on this platform is part of the Taipei Medical University Institutional Repository, featuring various academic works and outputs from the institution. It offers free access to academic research and public education for non-commercial use. Please use the content appropriately and within legal boundaries to respect copyright owners' rights. For commercial use, please obtain prior authorization from the copyright owner.

    • 瀏覽或使用本平台,視同使用者已完全接受並瞭解聲明中所有規範、中華民國相關法規、一切國際網路規定及使用慣例,並不得為任何不法目的使用TMUIR。

      By utilising the platform, users are deemed to have fully accepted and understood all the regulations set out in the statement, relevant laws of the Republic of China, all international internet regulations, and usage conventions. Furthermore, users must not use TMUIR for any illegal purposes.

    • 本平台盡力防止侵害著作權人之權益。若發現本平台之數位內容有侵害著作權人權益情事者,煩請權利人通知本平台維護人員([email protected]),將立即採取移除該數位著作等補救措施。

      TMUIR is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff([email protected]). We will remove the work from the repository.

    Back to Top
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回饋