隨著科技進步，高品質的醫療服務是民眾的期望，在中、西醫學思維路線及表達工具的差異，中醫系統中大都屬於隱藏性的知識，如何從各種資料庫及相關資料中、找出病情各種相關性的症狀從而歸納出它們可能的病情，則可幫助中醫師在診斷時之決策參考，是本研究主要問題與目的。 本研究提供整合型決策支援系統以資料倉儲為基礎，使用知識挖掘、資料探勘的技術及決策系統來建構病情分析決策支援系統；確定決策診斷知識方法下，將病患病情診斷分析法則經貝氏分類法產生疾病屬性歸類規則並經網路學習除錯與認知後，以決策樹產生診斷規則，導出診斷規則知識模型，再用診斷規則知識模型來驗證病情分析結果，其中使用資訊科技技術，若以此延伸運用到各個領域，將有很大發展空間。 最後，我們以一些實例用以驗證此模型及診斷規則的準確性，期望對中醫診斷系統提供另一思考方向。 As scientific technology is in progress, the desire of the public for a high quality of medical service is increasing. There is a difference in thinking processes and expression tools between Chinese and western medicine. Both medical systems belong to inner knowledge. Therefore, the objective of this study is to determine how to help Chinese medical doctors to make a decision in disease diagnosis on the basis of a variety of Database and related information from which possible disease-causing factors can be derived. This study support an integrated decision-supporting system based on the properties of Data Warehouse. The technique used are Knowledge Discovery, Data Mining and decision-making, in which a decision-supporting system can be obtained. Once the diagnosis is made through the knowledge-base decision, the patient's illness can be analyzed. On the basis of Bayer's classification, diseases can be classified. Through the learning of Bayesian Network to remove errors and make recognition, the Decision Tree could be obtained and the rule of diagnosis can be made. A knowledge model for diagnosis rule can be obtained on the basis of illness' analysis. In addition, this model can be used to analyze the disease by using the powerful interface from information technology. If this method can be applied to other fields, plenty of space for development will be made. Finally, we work out the practice on some real cases, and the system will be precisely made to analyze the consequence and predict patient's illness. We hope the Chinese -diagnosis system can provide another way of thinking in the field.
