Summarizing Professor Chen Ruquans Therapeutic Experience of Thyroid Disease Based on Machine Learning Objectives: To summarize the clinical experience of Professor Chen Ruquan in the treatment of thyroid disease. Technology or Method: All published literatures about Professor Chen Ruquan in the treatment of thyroid disease were searched and collected through computer retrieval; a comprehensive literature search was conducted from four databases including CNKI, VIP, WanFang Database, and China Biological Database. The clinical cases were extracted by applying NLP technology from the included literatures. The machine learning algorithms such as Association rules and Hierarchical Cluster analysis were applied through R software 3.6. Results: A total of 71 clinical cases for thyroid disease related with Professor Chen were included in the final analysis, involving 144 prescriptions with 190 herbs. The top three highfrequency drugs were Chi Shao (Radix Paeoniae Rubra), Gan Cao (Radix Glycyrrhizae) and Zhe Beimu (Bulbus Fritillariae Thunbergii). Nine pairs of couplet herbs and twenty four groups of 3herb combinations were respectively obtained. The cluster analysis showed that 8 groups of combinational herbs were obtained, 3 new prescriptions were acquired. Conclusions: Professor Chenu0027s ideology of syndrome differentiation and treatment was flexible and diverse, and innovated on the basis of syndrome differentiation of etiology combination with zangfu viscera. He treated thyroid diseases with many medicinal forms and took dispersing stagnated liver qi and removing blood stasis as treatment method and has received the good effect. Clinical or Biological Impact: This paper would help related scholars to uphold and deepen the research of inheriting the academic experience based on machine learning, and the effective clinical experience would be provided for young clinicians and even patients on the treatment of thyroid disease.

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.