Mining effect of Famous Chinese Medicine Doctors on Lungcancer based on Association rules Traditional Chinese medicine is a treasure house of the Chinese nation. Using data mining method to study traditional Chinese medicine can summarize the experience of traditional Chinese medicine and promote the development of traditional Chinese medicine. The doseeffect relationship of traditional Chinese medicine mainly refers to that the effect of drugs changes with the dose of drugs in a certain range, and there is a great relationship between the effect produced by different combinations of drugs and the dose of drugs. With the development of data mining technology, it is widely used to study the doseresponse relationship between drugs with the data of famous old traditional Chinese medicine doctoru0027s medical record. In this paper, based on the characteristics of traditional Chinese doctoru0027s medicine data, the Apriori algorithm is improved from the construction of the data model, so that the transaction database does not need to be converted into Boolean database in the mining, which can improve the reseracheru0027s friendliness. The results of the excavation not only included the common drugs used by famous tradional Chinese medicine doctors to treat lung cancer, but also analyzed the proportional relationship between the dosage of different drugs. To provide a reference for clinical researchers in the actual use of drugs between the proportion of the relationship.

Research on treatment and medication rule of insomnia treated by TCM based on data mining Objectives: Based on data mining technology, this research explores the rules of traditional Chinese medicine treatment of insomnia and obtains some significant medical implication through data mining. Technology or Method: Nearly 6,000 electronic medical records of Chinese medicine clinics are selected, and data preprocessing is performed. Then, Ariporiu0027s data mining algorithm is used to analyze prescription medication rule, and the association between symptoms and drugs. Finally, a network diagram is built through complex network analysis. Results: There are 631 insomnia cases that met the criteria, 22 typical symptoms, and 330 drugs. There are 6 symptom association items with a confidence level of more than 30%, 46 drug association items with a confidence level of more than 75%, and 40 symptom association rules with a confidence level of more than 40%. Conclusions: The results showed the rule of medication used in the diagnosis and treatment of insomnia in Chinese medicine outpatients, and found the association between prescription medication rules and symptomatic drugs. Clinical or Biological Impact: This paper provides a reference to the clinical diagnosis and treatment of young physicians, and provides a reference to the development of new drugs. And to promote the development of the theory and practice of traditional Chinese medicine prescriptions is conducive to inheriting and carrying forward the experience and advantages of Chinese medicine treatment of insomnia.