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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 盧信銘(Hsin-Min Lu) | |
| dc.contributor.author | Yu-Ching Chang | en |
| dc.contributor.author | 張郁卿 | zh_TW |
| dc.date.accessioned | 2021-06-17T02:12:11Z | - |
| dc.date.available | 2019-01-27 | |
| dc.date.copyright | 2018-01-27 | |
| dc.date.issued | 2017 | |
| dc.date.submitted | 2017-12-28 | |
| dc.identifier.citation | Bailey, N. T. (1955). Some problems in the statistical analysis of epidemic data. Journal of the Royal Statistical Society. Series B (Methodological), 35-68.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68074 | - |
| dc.description.abstract | 疾病傳播網路可以提供個人有效的資訊幫助保護自己，也可以幫助政府預防及控制感染疾病的擴散。目前有關傳染病的研究多侷限於小樣本、特定區域。本研究期望透過歷史醫療保險申報資料計算健康狀況時間序列，並以此建立疾病傳播網路。我們採用格蘭傑因果關係檢定以辨識目標群體與其他人之間潛在的傳播路徑。我們使用疾病傳播網路上鄰居的過去健保申報紀錄預測未來感染相似疾病事件來評估疾病網路的效果。與只使用個人過去歷史就醫紀錄的基準線模型相比，加入疾病傳播網路可以小幅度改善預測的表現。 | zh_TW |
| dc.description.abstract | Disease transmission network can provide important information for individuals to protect themselves and to support governments to prevent and control infectious diseases. Current studies on disease transmission network mostly focus on scenarios in small, confined areas. We propose to construct disease transmission network using health status time series computed based on health insurance claims. We adopted Granger causality tests to identify potential links from the health status time series from all pairs between target groups and other individuals. We evaluated our approach by predicting future health care seeking activates for similar diseases based on past health care seeking activates of neighbors in the disease network. Compared to baseline models that use only personal historical data, including the estimated transmission network can improve prediction performance. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T02:12:11Z (GMT). No. of bitstreams: 1 ntu-106-R04725008-1.pdf: 1789967 bytes, checksum: 0865560ad1915a2c58c0390d57b37620 (MD5) Previous issue date: 2017 | en |
| dc.description.tableofcontents | 摘要 I
ABSTRACT II 目錄 III 圖目錄 IV 表目錄 V 第一章 緒論 1 1.1 研究背景與動機 1 1.2 研究目的 2 1.3 研究問題 2 第二章 文獻探討 3 2.1 傳染病相關研究 3 2.2 疾病相似度 5 2.2.1 Latent Dirichlet Allocation (LDA) 5 2.3 疾病傳播路徑 9 2.4 預測模型 10 2.4.1 羅吉斯回歸模型 (Logistic Regression) 10 2.4.2 支持向量機 (Support Vector Machine，簡稱 SVM) 11 2.4.3 隨機森林 (Random Forest) 12 2.5 小結 12 第三章 實驗設計 13 3.1 實驗架構 13 3.2 資料來源 14 3.3 資料前處理 14 3.4 疾病主題萃取 16 3.5 格蘭傑因果關係檢定 18 3.6 預測感染事件 20 第四章 實驗結果 22 4.1 疾病主題數選擇 22 4.2 疾病傳播網路 23 4.3 預測得病 24 第五章 結論 29 5.1 結論 29 5.2 未來研究方向 29 參考文獻 30 附錄A 33 健保資料集健康狀況機率分佈 33 | |
| dc.language.iso | zh-TW | |
| dc.subject | 健保申報資料 | zh_TW |
| dc.subject | 健康狀況時間序列 | zh_TW |
| dc.subject | 疾病傳播網路 | zh_TW |
| dc.subject | Disease Transmission Network | en |
| dc.subject | Health Status Time Series | en |
| dc.subject | Health Insurance Claims | en |
| dc.title | 使用全民健保申報資料建構疾病傳播網路 | zh_TW |
| dc.title | Mining Disease Transmission Network in National Health Insurance Research Database | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳建錦,余峻瑜 | |
| dc.subject.keyword | 疾病傳播網路,健康狀況時間序列,健保申報資料, | zh_TW |
| dc.subject.keyword | Disease Transmission Network,Health Status Time Series,Health Insurance Claims, | en |
| dc.relation.page | 64 | |
| dc.identifier.doi | 10.6342/NTU201704524 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2017-12-29 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
| 顯示於系所單位： | 資訊管理學系 | |
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