Study on Medication Regularity of Famous TCM Doctors for Diabetes Based on Improved Apriori Algorithm
10.3969/j.issn.1005-5304.2017.12.024
- VernacularTitle:基于Apriori改进算法的名老中医治疗糖尿病用药规律研究
- Author:
qing An WAN
1
;
yang Jian BAO
;
fa Kong HU
Author Information
1. 南京中医药大学
- Keywords:
data mining;
association rules;
Apriori algorithm;
ADPM algorithm;
diabetes;
medication regularity
- From:
Chinese Journal of Information on Traditional Chinese Medicine
2017;24(12):97-101
- CountryChina
- Language:Chinese
-
Abstract:
Objective To analyze the medication regularity of TCM famous doctors for diabetes by using improved Apriori algorithm to obtain more efficient data mining methods. Methods This article put forward Apriori vertical data storage, and improved ADPM obtained by difference set method was used to conduct data mining to find out the medication regularity in Guo Jia Ji Ming Lao Zhong Yi Tang Niao Bing Yan An Liang Fang. Results After screening, 402 prescriptions were included, involving 24 kinds of high-frequency medicine, 15 high-frequency medical combinations, and 18 highly-dependent medical combinations, which were mainly tonifying deficiency medicine, clearing heat medicine, blood-activating and stasis-resolving medicine, and damp-draining diuretic medicine. Conclusion ADPM algorithm can be applied in the analysis on medication regularity and find out high-frequency medicine, medical combinations and medical dependent relation, with high efficiency.
