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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 翁昭旼(Jau-Min Wong) | |
dc.contributor.author | Zhen-Yu Wu | en |
dc.contributor.author | 吳鎮宇 | zh_TW |
dc.date.accessioned | 2021-06-08T02:39:58Z | - |
dc.date.copyright | 2018-06-21 | |
dc.date.issued | 2016 | |
dc.date.submitted | 2018-05-30 | |
dc.identifier.citation | [1]行政院環境保護署,河川水質監測資料 http://erdb.epa.gov.tw/FileDownload/FileDownload.aspx
[2]Yvon Motreff, Franck Gollio, Michel Calleja, Annick Le Pape, Claire Fuhrman, Isabelle Farrera, Isabelle Plaisant. Short-term effect of pollen exposure on drug consumption for allergic rhinitis and conjunctivitues. Aerobiologia (2014) 30:35–44. [3]Kun Chen, Weiping Yu, Xinyan Ma, Kaiyan Yao, Qinting Jiang. The association between drinking water source and colorectal cancer incidence in Jiashan County of China: a prospective cohort data. European Journal of Public Health. Vol. 15, No. 6, 652-656 [4]Jane A. McElroy, Amy Trentham-Dietz, Ronald E. Gangnon, John M. Hampton, Andrew J. Bersch, Marty S. Kanarek and Polly A. Newcomb. Nitrogen-nitrate exposure from drinking water and colorectal cancer risk for rural woman in Wisconsin, USA. Journal of Water and Health. 06.3, 2008, 399-409 [5]Nitrate/Nitrite - ToxFAQs™, ATSDR(Agency for Toxic Substances and Disease Registry) [6]國家環境毒物研究中心,硝酸鹽與亞硝酸鹽(中譯版) http://nehrc.nhri.org.tw/toxic/toxfaq_detail.php?id=187 [7] Curt T. DellaValle, Qian Xiao, Gong Yang, Xiao Ou Shu, Briseis Aschebrook- Kilfoy, Wei Zheng, Hong Lan Li, Bu-Tian Ji. Nathaniel Rothman, Wong-Ho Chow, Yu-Tang Gao, and Mary H. Ward. Dietary nitrate and nitrite intake and risk of colorectal cancer in the Shanhai Woman's Health Study. NIH Public Access. Int J Cancer. 2014 June 15; 134(12): 2917–2926. doi:10.1002/ijc.28612. [8]全民健保研究資料庫,資料庫內容-說明 http://nhird.nhri.org.tw/date_01.htm [9]台中市環境保護局環境教育宣傳網,何謂河川汙染指數(RPI) http://ww2.epb.taichung.gov.tw/education/learning_detail.asp?key=98&page=3 [10]行政院環境保護署,自來水水質抽驗資料 http://erdb.epa.gov.tw/DataRepository/EnvMonitor/WaterQualityTestData.aspx [11]S. Kotsiantis, D. Kanellopoulos, P. Pintelas, 'Data Preprocessing for Supervised Learning', International Journal of Computer Science, 2006, Vol 1 N. 2, pp 111–117. [12]Data Mining, Concept and Techniques, Jiawei Han and Micheline Kamber http://www.cs.sfu.ca [13]衛生福利部中央健康保險署,疾病分類代碼及範圍 http://www.nhi.gov.tw/webdata/webdata.aspx?menu=18&menu_id=798&WD_ID=798&webdata_id=1008 [14]ICD-9代碼查詢(中文版) http://icd-9.blogspot.com/ [15]全民健保研究資料庫,編碼簿B,B-13地區代碼、名稱、分局及郵遞區號 [16]衛生福利部統計處,年齡分層參考 http://www.mohw.gov.tw/cht/DOS/Statistic.aspx?f_list_no=312&fod_list_no=2218 [17]Breslow, N. E. (1975). Analysis of Survival Data under the Proportional Hazards Model. International Statistical Review / Revue Internationale de Statistique 43 (1): 45–57.doi: 10.2307/1402659. JSTOR 1402659 [18]Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers, 2nd Edition Roy D. Yates (Rutgers University, NJ), David J. Goodman (Polytechnic University, NY) [19]GLM for Poisson Data, Division of Biostatistics and Epidemiology Medical University of South Carolina. Dipankar Bandyopadhyay, Ph.D. [20]DeGroot, Morris H. (1986). Probability and Statistics (Second ed.). Addison- Wesley. pp. 258–259. [21]Hilbe, Joseph M. (2011). Negative Binomial Regression (Second ed.). Cambridge, UK: Cambridge University Press. [22]Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models. William H. Greene. March, 1994. [23]AIC v.s. BIC, The Methodology Center https://methodology.psu.edu/eresources/ask/sp07 [24]Akaike H. A new look at the statistical model identification. IEEE Trans. Automat. Contr. AC-19:716-23, 1974. [Institute of Statistical Mathematics, Minato-ku, Tokyo, Japan] [25]Cryptography Theory and Practice. Stinson. 2nd edition. Chapter 2-4. [26]Interpreting Residual and Null Deviance in GLM R http://stats.stackexchange.com/questions/108995/interpreting-residual-and-null-deviance-in-glm-r [27]Paul Knekt, Ritva Jarivinen, Jan Dich and Timo Hakulinen. Risk of colorectal and other gastro-intestinal cancers after exposure to nitrate, nitrite and N-nitroso compounds: a follow-up study. Int. J. Cancer: 80, 852–856 (1999) [28]不可忽視的癌症殺手-大腸直腸癌,大腸直腸癌防治團隊/謝宏濱主任(2007) [29]Understanding Colon Cancer. A. Richard Adrouny, M.D., F.A.C.P. [30]Introductory Statistics with R, Second Edition. Peter Dalgaard. [31]R documentation. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/20093 | - |
dc.description.abstract | 環境中各種因子,都有可能影響某個疾病的發生率,因此本研究整合不同的資料庫並做數據分析,來討論某些因子是否與某些疾病有關連性。
本研究採用國家衛生研究院的全民健康保險研究資料庫(NHIRD)與行政院環保署的水質監測資料庫做整合,疾病因子取大腸直腸癌、水質資料取河川汙染程度指標(RPI)來做對數線性模型的回歸分析,藉由回歸式的擬合來探討大腸直腸癌發生率在各年齡層、各年份與水質好壞的關連性,最後再將自來水中硝酸鹽氮與亞硝酸鹽氮的監測值放入回歸式探討其關連性,並與現有文獻做比較。 其中可以看出水質好壞與大腸直腸癌發生率成低度正相關,另外分別對地區與水質、年齡層、年份做分析,探討哪些缺點影響擬合程度,並提出可行的解決方案供未來在此方面繼續研究之研究者一個修正方向。 最後分析出來的數據結果,可供其他領域做更進階的研究,以大數據的趨勢來供研究者提出假說的方向,以減少實驗重複驗證的時間。 | zh_TW |
dc.description.abstract | Environmental factors may influence the incidence of certain diseases. This research integrates different databases to analyze the notation of these factors with diseases.
To integrate National Health Insurance Research Database(NHIRD) and Water Quality Database of Taiwan. We use Poisson loglinear regression model try to analyze the connection between incidence of colorectal cancer and River Pollution Index(RPI) in the aspects of different geographic area, age group and year influence. Besides, we also use pipe water concentration data of nitrate and nitrite nitrogen in the regression model to confirm if these factor has positive correlation with the incidence of colorectal cancer. By this way, we can find those modestly correlated attributes between incidence of colorectal cancer and River Pollution Index(RPI). Also, we can analyze them in the aspects of water quality, different area variable, age group, and time trend in year to discuss what reasons are related to the goodness of fit. At least, these results may provide future researchers in related fields with some useful information. Researchers can also use the concept of big data analysis to propose a new project in their proposal. | en |
dc.description.provenance | Made available in DSpace on 2021-06-08T02:39:58Z (GMT). No. of bitstreams: 1 ntu-105-R03548032-1.pdf: 2066068 bytes, checksum: 23fd3efce3e28bfe69175c22022dc985 (MD5) Previous issue date: 2016 | en |
dc.description.tableofcontents | 誌謝 I
中文摘要 II ABSTRACT III 目錄 IV 圖目錄 VI 表目錄 VII 第一章 緒論 1 1.1研究背景與動機 1 1.2研究目的 1 1.3研究流程 2 第二章 相關文獻探討 3 第三章 研究材料 6 3.1健保資料庫 6 3.2水質監測資料庫 7 3.3自來水水質抽驗資料庫 8 第四章 研究方法 9 4.1資料預處理(DATA PREPROCESSING) 9 4.1.1資料清理(Data Cleaning) 10 4.1.2資料整合(Data Integration) 11 4.1.3資料轉換(Data Transformation) 11 4.1.4資料精簡(Data Reduction) 12 4.2數據總表處理與格式 13 4.3統計回歸模型 15 4.3.1卜瓦松對數線性模型(Poisson Loglinear Model) 15 4.3.2負二項回歸模型(Negative Binomial Regression Model) 19 4-4誤差討論項目 20 4-4-1赤池信息量準則(Akaike information criterion, AIC) 20 4-4-2殘差離異統計量(residual deviance) 21 第五章 分析結果與問題討論 22 5.1使用卜瓦松對數線性模型的分析結果 22 5.1.1使用RPI連續資料 22 5.1.2使用RPI類別資料 25 5.1.3改良RPI類別資料 26 5.1.4交互作用項的討論 28 5.2使用負二項回歸模型的分析結果 33 5.3回歸式與現實狀況的討論 35 5.3.1地區(area)與水質(RPI)的影響 35 5.3.2年齡層(age)的影響 39 5.3.3年份(year)的影響 40 5.4加入硝酸鹽氮(NO3N)與亞硝酸鹽氮(NO2N)的討論 41 5.5討論 44 5.5.1時間延遲(time delay) 44 5.5.2人口遷徙 44 5.5.3水源取樣 45 5.5.4發生率的低估 45 5.5.5抽樣偏差 45 第六章 未來展望 46 附錄 47 附錄一 數據總表截圖 47 附錄二 統計分析程式碼 48 附錄三 卜瓦松對數線性模型的擬合結果 51 附錄四 負二項回歸模型的擬合結果 54 參考文獻 57 | |
dc.language.iso | zh-TW | |
dc.title | 水源監測資料庫與健保資料庫之整合巨量數據分析 | zh_TW |
dc.title | Application of Big Data Analysis in Integration of Water Quality Database and National Health Insurance Research Database | en |
dc.type | Thesis | |
dc.date.schoolyear | 106-2 | |
dc.description.degree | 碩士 | |
dc.contributor.coadvisor | 蔣以仁(I-Jen Chiang) | |
dc.contributor.oralexamcommittee | 張淑惠(Shu-Hui Zhang) | |
dc.subject.keyword | 健保資料庫,水質監測資料庫,大腸直腸癌,河川汙染程度指標,對數線性模型, | zh_TW |
dc.subject.keyword | NHIRD,Water Quality Database,Colorectal Cancer,RPI,Loglinear Model, | en |
dc.relation.page | 59 | |
dc.identifier.doi | 10.6342/NTU201601362 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2018-05-31 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 醫學工程學研究所 | zh_TW |
顯示於系所單位: | 醫學工程學研究所 |
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