| ObjectiveBased on the Chinese classic literature and medical records of Chinese famous doctors, this research tries to construct a "Disease-Syndrome-Treatment" (DST) data knowledge base through extract the diseases, symptoms, clinical decision (prescription and herb). Besides, use the knowledge discovery method of big data based on structural partial-ordered attribute theory for further analysis, identification, validation and application. This research hopes to realize the scientific classification of different states and stage of disease and syndrome, find the accurate corresponding rules of DST, optimize the medical procedures and clinical practice of treatment based on syndrome differentiation; put forward and preliminary practice the feasible mode of "Precision Traditional Chinese Medicine".MethodsCompared with the research mode of "Precision Medicine", put forward the mode of "Precision Traditional Chinese Medicine" which is based on the knowledge discovery method of big data based on structural partial-ordered attribute theory. And then based on the Chinese classic literature and medical records of Chinese famous doctors, symptomatic nouns as breakthrough point, put the mode into practice.Using Treatise on Febrile Diseases, Chinese classic literature, as example, on the basis of respect the original clauses, extract and standardized expression of the symptom and syndrome in the original clauses, this research tries to construct a DST knowledge database of the Treatise on Febrile Diseases and to realize the quality control of it. Besides, use the knowledge database as object and the method of big data based on structural partial-ordered attribute theory, to generate a comprehensive, systematic and multi-level structural partial-ordered attribute diagram of the "Disease-Syndrome-Treatment-Prescription" (DSTP) and structural partial-ordered object diagram of the "Disease-Syndrome-Treatment-Prescription-Herb" (DSTPH) in Treatise on Febrile Diseases. Furthermore, explain the diagram to fulfill the reliable and reasonable knowledge discovery.In the second part, collect medical records from Professor Saimei Li, in the First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, during the period of May 2015 to October 2015. Though the data screening, standardized expression, curative effect evaluation, quality control, review and assessment, construct a DST data knowledge base of Professor Saimei Li. Then, use this knowledge database as object and the method of big data based on structural partial-ordered attribute theory, to generate a comprehensive, systematic and multi-level DST structural partial-ordered attribute diagrams, and explain the diagram reasonable to fulfill the reliable and reasonable knowledge discovery.ResultsAccording to the established DST knowledge database of the Treatise on Febrile Diseases, use 100 prescriptions as object,182 diseases and syndromes as attributes, to construct the general structural partial-ordered attribute diagram of DSTP. Use 100 prescriptions as object,84 kinds of herbs as attributes, to construct the general structural partial-ordered object diagram of DSTPH. Then, according to the sequence of frequency, choose the first five concepts (fever, diarrhea, vomiting, constipation, abdominal distension) for specific analysis, following the corresponding each disease-syndrome branches of the DSTP structural partial-ordered attribute diagram to judge and exclude, obtain the accurate prescription; and use the prescription to testify the syndrome, through the second data mining, discover the corresponding disease-syndrome situation of Zhongjing treated; combined with the corresponding "Treatment-Prescription-Herb" structural partial-ordered object diagram, the prescription can be assigned to specific herbs, showing the rules of application of prescription and medication. Meanwhile, make visible display of structural partial-ordered diagram for the concepts of abdominal pain, headache, cough, asthma, insomnia and so on.According to the established DST knowledge database of medical records of Saimei Li, and according the characters (constipation, diarrhea, fever, abdominal fullness, vomiting) divided into five categories and construct corresponding DST structural partial-ordered attribute diagram respectively; ollowing the corresponding each disease-syndrome branches of the DST structural partial-ordered attribute diagram to judge and exclude, obtain the accurate prescription; and use the prescription to testify the syndrome, through the second data mining, discover the corresponding disease-syndrome situation of Saimei Li treated.ConclusionWith the concept of "Precision Medicine" promoting globalization, the entire medical industry meet a new reform. The contemporary Chinese physicians consider rational in this reform trend, survey the inner meaning of TCM, dig the opportunities for development, and make greater contributions to human health. This research compared with essence of "Precision Medicine", based on the theory of knowledge discovery method of big data based on structural partial-ordered attribute method, put forward the feasible mode of "Precision Traditional Chinese Medicine". Besides, use the Treatise on Febrile Diseases and medical records of Saimei Li as example, testify the feasibility of the mode. And if further practice and improve the mode, it will promoting the development of precision TCM and making patients benefited furthest. |
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