疾病症状与类型关系的苗医药大数据挖掘方法

苗族文字的缺失造成了苗药药效记录的缺失，从而影响苗药的规范研制和科学用药.苗医药大数据挖掘通过分析病历中疾病与用药之间的关系挖掘出苗药药效，为苗药药效记录的缺失问题提供了新的解决思路.然而由于各地苗医的技术水平参差不齐，苗医在分辨疾病时会出现偏差,这给从苗医药大数据中挖掘出苗药药效造成了困难.针对病历数据中疾病分类存在偏差的问题，本研究提出了一个基于分布式k近邻的、面向疾病症状与类型关系的苗医药大数据挖掘方法.实验结果表明在数据量大的情况下该方法具有较高的分类准确度.

Miningmethod of symptoms and disease relationship based on big data in Miao medicine

The lack of Miao characters leads to the lack of efficacy of Miao medicine,so as to affect the development and scientific use of Miao medicine.The Big Data in Miao medicine provides a new way to solve the problem of lack of drug properties.Efficacy of Miao medicine can be found by analyzing the relationship between disease and drug use in medical records.However,because of poor medical technology,some Miao-nationality doctors gave wrong disease when they handled some cases.As wrong disease,it is difficult to mine the efficacy of Miao medicine from the Big Data in Miao medicine.For wrong disease,this paper presents a mining method of Miao medicine symptoms and disease based on distributed k nearest neighbor.In the case of large amount of data,the method has good classification performance and high accuracy.