博碩士論文 107826012 詳細資訊

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姓名 余佳杭(Chia-Hang Yu)  查詢紙本館藏   畢業系所 系統生物與生物資訊研究所
論文名稱 以地區醫院病例探討桃園之地域族群與疾病之差別
(Investigation of the Differences between Regional Groups and Diseases in Taoyuan from the Regional Hospital Records)
★ 細菌物種基因體中非編碼小片段核糖核酸之預測★ 從年齡動態網路探討疾病盛行率
★ 藉由比較基因表現資料研究次世代定序與晶片技術分析差異★ 啟動子甲基化與對應之基因表現微陣列資訊整合分析
★ 乾燥綜合症與非病毒型肝炎之相關因子分析★ 氣候變遷對人類疾病網路造成衝擊
★ 台北和中壢地區不孕症分佈與共病探討★ 探討台灣的門診疾病與環境空氣品質的濃度變化之相關性
★ 桃園地區之區域與疾病盛行率之關聯★ CyTOF之生物標記篩選與分析
★ 透明細胞腎細胞癌質譜流式細胞儀資料分析與視覺化★ 使用支持向量機預測蛋白質醣基化位置
★ 使用基因表現資料預測基因轉錄調控網路★ RNA Riboswitch搜尋系統之設計與實作
★ 人類疾病差異表現基因與調控網路之整合系統★ 利用赫伯特-黃轉換法辨識酵母菌在呼吸/還原週期中的震盪基因群
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摘要(中) 在近年,大數據研究已經逐漸成為顯學。利用資料探勘分析我們能夠找尋不同因子間互相的關聯,藉由數據佐證猜測。在醫學領域方面,我們能夠觀察疾病與可能因子間的關係。根據這些結果,可以為我們提供策略改善醫療,增進未來生醫領域的進步。
摘要(英) In recent years, big data research has gradually become a prominent study. Using data mining, we can find the correlation between different factors, and use data to support the guess. In the medical field, we can observe the relationship between disease and possible factors. Based on these results, it can provide us with strategies to improve medical care and enhance the progress in the field of biomedicine in the future.
Our laboratory cooperates with Landseed Hospital to obtain their outpatient data over the years. The information includes the patient′s age, gender, education level and place of residence. With these large amounts of outpatient data, we can use machine learning methods for patient group and filter useful rules.
We focus on the prevalence of Taoyuan in different places of residence. We divided the Taoyuan area into coastal and inland areas according to the administrative area classification, and used decision trees to discuss the differences in the prevalence of residents in the two areas. Judging the significance of the study method, and finally screening out the demographic groups with significant differences in disease in the two regions.
The main reasons for the difference in the prevalence between coastal and inland areas around the world are environmental pollution, eating habits, urban-rural gaps, natural disasters, personal habits, etc. We compared the results of the Taoyuan area with the results of other parts of the world, and cross-examined the reasons for the difference in the prevalence of coastal and inland areas in the Taoyuan area.
Give the results to the regional hospitals for reference, so that the regional hospitals can provide corresponding medical care and programs for these special demographic groups in the future.
關鍵字(中) ★ 機器學習
★ 資料探勘
★ 關聯性
★ 門診疾病
★ 地域差異
★ 電子資料庫
關鍵字(英) ★ Machine learning
★ Data mining
★ Relevance
★ Outpatient disease
★ Regional difference
★ Electronic database
論文目次 Chinese abstract i
English abstract ii
List of Figures v
List of Tables vi
Chapter 1 Introduction 1
1-1 Motivation and Goal 1
1-2 Landseed′s outpatient database 2
Chapter 2 Methods and Material 3
2-1 Flow chart and methods 3
2-2 Data preprocessing 4
2-2-1 Data cleaning 4
2-2-2 Combine data into categories 4
2-2-3 Gender 5
2-2-4 Age level 5
2-2-5 Education level 5
2-2-6 Coastal or not 6
2-2-7 Disease history 6
2-3 WEKA 7
2-4 Decision tree 8
2-5 Database sampling 8
2-6 Category cross analysis 9
2-6-1 Relative risk and Odds ratio 9
2-6-2 Chi-square test and Yates correction 10
Chapter 3 Results 12
3-1 Basic statistics 12
3-2 Decision tree 14
3-2-1 Original data gram 14
3-2-2 Smaller data gram 22
Chapter 4 Discussion 27
References 28
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指導教授 吳立青(Li-Ching Wu) 審核日期 2020-8-20
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