基于数据挖掘预防新型冠状病毒肺炎中医方药初探

Preliminary study of traditional Chinese medicine for preventing COVID-19 based on data mining

运用中医传承辅助平台(V2.5)挖掘分析各省市新型冠状病毒肺炎(COVID-19)预防方药,总结探讨其潜在新方。收集检索国家及各省、自治区和直辖市卫健委、中医药管理局官方网站关于COVID-19中医药预防方案,得到黑龙江、北京、天津、河北、河南、江西、四川、湖北、湖南等17个省市的COVID-19中医药预防方案,运用频次统计、关联规则、基于熵聚类方法规律分析等方法进行药物规律及特点的挖掘。64首处方中共包含82味中药,使用频次较高的中药为黄芪、金银花等,补虚药使用最多,多用甘、温之品,归肺经药物最多;通过关联规则分析,得到8个常用药物组合;基于熵聚类方法规律分析得到7个潜在新方。各地多使用补虚扶正药物预防COVID-19,多从肺、脾胃着手,虽具体细节不同,但都体现了中医学的预防思想。

To dig out and analyze the drug rule of COVID-19 prevention prescriptions from provinces and cities by using Traditional Chinese Medicine Inheritance Support System,summarize and explore its potential new prescription.The Chinese medicine prevention programs for COVID-19 were collected and searched from the official website of the Health Commission and State Administration Medicine of Traditional Chinese Medicine of the country and provinces,autonomous regions,and municipalities.TCM prevention programs in 17 provinces including Heilongjiang,Beijing,Tianjin,Hebei,Henan,Jiangxi,Sichuan,Hubei,and Hunan,etc were received.A total of 82 herbs were included in 64 prescriptions,the most frequently used Chinese herbs were Astragalus membranaceus,Lonicera japonica,etc.Tonifying deficiency drugs with sweet and warm natures were used the most,the Chinese herbs distributed in the lung channel was the most in channel tropism drugs.Analysis by association rule,eight combinations of commonly used drugs were obtained.Based on entropy clustering method rule analysis,seven potential new prescriptions were obtained.Tonifying deficiency drugs are often used in various places to prevent COVID-19,focusing on the lung,spleen and stomach.Although the specific details are different,they all reflect the preventive thinking of traditional Chinese medicine.