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歷 年 稿 件 內 容
 
*類別：
* 姓名： 鄭詠慈
投稿種類： 壁報
*中文投稿標題： 以資料探勘技術建立自體免疫疾病診斷決策支援系統
*中文作者姓名列：
*中文服務單位：
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*英文服務單位：
* 投稿摘要： Autoimmune diagnostic assays are essential for determination of autoimmune diseases. Antinuclear antibody (ANA) , double strand DNA antibody (anti-dsDNA) and extractable nuclear antigens antibody (anti-ENA) are basic examinations in diagnosis of autoimmune diseases. Because immunofluorescence method is still the gold standard of ANA screening for it could display the diversity and variety of autoantigens. It’s important to set up a decision support system to assist diagnosis in autoimmune disease. Data mining concept was introduced and both hierarchical clustering analysis and C4.5 algorithm were applied to analyze the database contains 13062 ANA (titer and pattern), Anti-dsDNA (quantative) and Anti-ENA (RNP, Sm, Ro, La, Scl) assay results in Cathay General Hospital. Age, sex and diagnosis code were also included in data attributes. 4844 ANA positive data with anti-dsDNA and anti-ENA results were processed by data mining method as training set and the prediction model outputs were visualized in tree diagrams. Bottom-up dendrogram is generated by hierarchical clustering to display the differences and associations between clusters. Top-down decision tree is produced by C4.5 algorithm to show the classifications of data attributes. These information processing strategies and prediction models could support physician in adjusting appropriate treatment or choosing further examinations according to the latest autoimmune disease test reports and evolutionary computation association rules.
*關鍵字1 ： autoimmune disease
*關鍵字2 ： decision support system
*關鍵字3 ： data mining
*關鍵字4 ： dendrogram
*關鍵字5 ： association rule
* 服務機關：
* 第一作者： 鄭詠慈
* 身分字號： *****18606
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