基于数据挖掘的中医诊疗研究进展

Research Progress in Data Mining-Based TCM Diagnoses

中医在对疾病的治疗中发挥着重要的作用,为我国国民健康做出了巨大的贡献。然而,中医诊疗过程中存在着的主观性、模糊性以及不规范性等问题,给中医可持续研究发展提出了严峻的挑战。为解决这一挑战,有学者提出基于数据挖掘的中医临床诊断方法,探索中医治疗的本质规律。综述基于数据挖掘的中医诊疗方法,总结当前最新研究情况,阐述数据挖掘方法在促进中医诊疗的客观化与标准化上的成果。首先总结面向中医诊疗的主要数据挖掘方法,介绍了算法的特性以及其在中医诊疗中的适用场景。在此之上,以用药规律、证型判断以及方证关系3个方面为论述角度,系统地阐述了数据挖掘算法在中医诊疗中的最新研究进展。最后,针对数据挖掘算法在中医诊疗应用中亟须改进的问题,提供一些潜在研究思路。

Traditional Chinese medicine(TCM) plays an important role in the treatment, which has made great contributions to the health of people. However, the subjectivity, ambiguity and irregularity of the TCM diagnoses have posed vast challenges to the sustainable development of TCM. To solve those challenges, some data mining-based TCM diagnosis methods are proposed, well exploring the essential rules hidden in the TCM treatment. The paper reviewed the recent data mining-based TCM diagnosis methods and expounds the impressive results of data mining-based methods in promoting the TCM diagnosis objectification and standardization. In particular, the paper summarized the data mining methods which were widely used in TCM diagnoses, by introducing the algorithm characteristics and the TCM application scenarios. And then, the paper systematically explained the latest research progress in the data mining-based TCM diagnoses from the perspectives of compatibility laws of prescriptions, the diagnosis of syndrome and relationships between prescriptions and syndromes. Finally, some future research problems in the data mining-based TCM diagnosis were provided.