云环境下海量方剂组方规律分析

Analysis of Mass Prescriptions of Chinese Medicine in Cloud Environment

目的:结合云计算技术对海量方剂数据进行关联分析,揭示其内在的组方规律。方法:研究云环境下分析海量数据的关键技术,构建方剂组方数据的指标体系,结合Map Reduce编程模型对Apriori算法进行改进,设计并利用基于云计算的海量方剂组方规律分析平台对方剂数据进行关联分析。结果:以海量方剂组方数据为例,探索方剂组方的一般规律,得出方剂药物间和症状与药物间的关联关系。结论:研究结论与实际应用相符,在一定程度上揭示了病证方药的内在规律,可以为临床病证辨证论治、遣药组方提供依据。在计算效率方面,云平台具有明显优势。

This study aimed to reveal the regularity of prescription data of tradition Chinese medicine（TCM） using cloud computing technology. Key technologies for analyzing massive data in the cloud environment were adopted. Then the index system of prescription data of TCM was set up. Combined with a programming model that named Map Reduce, Apriori algorithm was improved in this study. And analysis platform for mining rules of massive prescription data were designed and used in association analysis. As a result, taking massive prescription data for instance, general rules of prescriptions were explored; and the association links among prescription drugs, and incidence relation between symptoms and medicines were obtained. Experiment outcomes demonstrated that this conclusion was consistent with the actual application, which revealed the inherent discipline of diseases and prescriptions, and provided references for clinical diagnosis and prescription compatibility. In addition, cloud platform had obvious advantages in computational efficiency.