目的：通过使用隐树模型对症状数据进行分析，为西医疾病的辨证分型提供证据，初步建立辨证分型方案和辨证规则。方法：本文为一个文章系列的第3 篇，前两篇论文探讨了通过分析症状数据为辨证分型提供证据的基本原理，展示了隐树分析可以系统地揭示数据不同侧面，并且提出基于数个相关侧面对患者群进行综合聚类，获得辨证分型方案。本文以综合聚类的结果为出发点，提出一种建立辨证分型规则的方法。结果：使用该法对一组血管源性轻度认知障碍数据进行研究，获得辨证分型方案和相应的辨证规则。结论：通过一系列文章构建一套研究西医疾病之辨证分型的完整方法，遵循该法以从疾病患者群的症状数据出发，最终得到辨证分型方案和辨证规则。

Objective: In China, doctors at TCM hospitals and clinics often divide patients with a Western medicine(WM) disease into several syndrome classes from the TCM perspective and treat patients in different classes using different principles. A key problem is how to carry out the classification properly. We propose an evidence-based approach for solving the problem where evidence is obtained by analyzing unlabeled symptom data using latent tree models.Method: In previous work, we have shown how latent tree analysis of symptom data can be used to identify TCM syndrome classes among patients with a WM disease. In the paper, we investigate how to establish classification rules for distinguishing between the classes.Results: We have applied the method to a data set about Vascular Mild Cognitive Impairment that involves 93 symptoms and 803 patients. Nine syndrome types are identified, along with the corresponding classification rules. Conclusions: An evidence-based approach to the TCM patient classification problem has been developed. The approach can be used to answer the following questions about a WM disease: What TCM syndrome classes are there? What are the sizes of the classes? What are the statistical characteristics of each class? How can one differentiate between the different classes?

科学技术部中医药行业科研专项（200807011）：老年期轻度认知障碍社区辨识、筛查及中医干预项目，负责人：张允岭；科学技术部中医药行业科研专项（201007002）：中医防治中风病技术转化与社区推广研究-中风后认知障碍社区中医药防治与管理研究，负责人：张允岭；北京市教育委员会新医药学科群建设项目（XK100270569）：基于健康医学模式的社区慢病防护及康复研究-老年期轻度认知障碍社区筛查 及中医药防治研究，负责人：张允岭。