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知識發掘法應用於B-code證型類別之決定-以紅斑性狼瘡患者為例

Knowledge Discovery Technology for Determining the Disease Pattern in B-code-The Data from SLE Patients

摘要


本文運用知識發掘法之潛在群體分析,配合中醫疾病分類辨證編碼系統(B-code),對系統性紅斑性狼瘡(Systematic Lupus Erythematosus; SLE)之臨床診療進行知識發掘。本文利用B-code對現有SLE病症患者之辨證進行資料整理,並運用潛在群體分析法進行分類,找出經常出現之證型類別。本文之研究結果經資深中醫師驗證發現,運用潛在群體分析得出之證型類別可做為中醫臨床使用。進一步並可將此證型類別之判斷準則,做為建立SLE診療輔助系統雛型之依據。

並列摘要


In this study, the latent class analysis in knowledge discovery technologies and disease pattern coding system of traditional Chinese medicine (i.e., B-code) are applied to discover important medical knowledge and their relationship. The data from Systematic Lupus Erythematosus (SLE) patients are rearranged with B-code and the latent class analysis is then used to cluster the commonly occurred disease patterns of SLE by B-code. The research results are verified by senior doctors of Chinese medicine and show that the disease patterns by latent class analysis are helpful for the Chinese clinical. In addition, the decision rule of disease patterns is the basis for constructing the medicinal aid system of the SLE.

參考文獻


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