Abstract Objective To explore the cases related to measles epidemic disease recorded in ancient medical books of the Qing Dynasty based on association and clustering rules, and to provide diagnosis and treatment ideas for clinical prevention and treatment of acute infectious diseases. Methods “Measles” related medical cases Chinese Medical Canon in the Qing Dynasty were retrieved, and the cases were screened according to inclusion and exclusion criteria. A database was established via Excel to perform data collation, induction, and statistical analysis for frequency. SPSS software was used to conduct correlation and cluster analysis for high-frequency drugs. Results High-frequency drugs were Linderae Radix, Citri Reticulatae Pericarpium Viride, Asari Radix Et Rhizoma, and so on. In the aspect of four qi, the occurrence frequency of cold drugs and the usage frequency of warm drugs were the highest; in the aspect of five tastes, occurrence frequency of drugs in bitter, sweet, and spicy were high, while the most usage frequency of drugs in bitter and spicy were high; in the aspect of meridian passage, the occurrence frequency of drugs in lung, stomach, and liver meridian was high; the usage frequency of drugs in liver, lung, and spleen was high. High frequency of symptoms had fever, abdominal pain, dizziness, and so on. The drugs were divided into six groups according to the distance between the groups and the efficacy of the drugs. Conclusion Measles epidemic disease is often accompanied by fever, abdominal pain, dizziness, and other symptoms, treatment should eliminate stasis and promote measles drainage, disperse with pungent medicinals and descend with bitter medicinals. The analysis of the basic prescriptions in different stages of ancient books of the Qing Dynasty can provide effective diagnosis and treatment ideas for the prevention and treatment of traditional Chinese medicine epidemic diseases.
LIN Xueyu LI Jian MA Yuan ZHANG Wenfeng. Research on the rules of measles epidemic disease diagnosis and treatment based on data mining[J]. 中国医药导报, 2022, 19(19): 142-145.
