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Multi-content implicit Dirichlet distribution model and traditional Chinese medicine case implicit pathogenesis mining method

A technology of implicit Dirichlet and distribution model, applied in the fields of medical data mining, medical informatics, medical practical experience/guidance, etc., can solve the problem of rare hidden pathogenesis

Inactive Publication Date: 2019-10-01
EAST CHINA NORMAL UNIV
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Problems solved by technology

Research on unearthing hidden pathogenesis through the link between disease and drug is relatively rare

Method used

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  • Multi-content implicit Dirichlet distribution model and traditional Chinese medicine case implicit pathogenesis mining method
  • Multi-content implicit Dirichlet distribution model and traditional Chinese medicine case implicit pathogenesis mining method
  • Multi-content implicit Dirichlet distribution model and traditional Chinese medicine case implicit pathogenesis mining method

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Embodiment 1

[0078] In the present invention, the data is preprocessed first, and the data contains several medical records. Each medical record includes a line of symptom words separated by a separator, and a line of medicine words separated by a separator. The number of symptom words and drug words in each medical record is not fixed. In this embodiment, there are a total of 900 medical records.

[0079] Then, set the number of disease machines K. In this embodiment, K=10.

[0080] Refer to the above Gibbs sampling steps and repeat the iteration until the Gibbs sampling process converges. In this embodiment, the number of iterations is set to 1000.

[0081] In practical applications, you can also set the number of iterations to speed up the convergence speed and ensure that the accuracy of the model is not affected.

[0082] Table 1: A medical record document in this embodiment

[0083]

[0084] After the sampling is completed, the present invention obtains the parameter values ​​in this embod...

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Abstract

The invention provides a multi-content implicit Dirichlet distribution model, a construction method of the multi-content implicit Dirichlet distribution model and an implicit pathogenesis mining method of a traditional Chinese medicine case by utilizing the model. According to the invention, the method comprises the steps: taking each traditional Chinese medicine case as a word containing a groupof symptoms and a group of corresponding medicine words, giving a solving method of model parameters based on the multi-content implicit Dirichlet distribution model, and finally obtaining a pluralityof symptoms and medicines belonging to the same pathogenesis. According to the method, the traditional Chinese medicine diagnosis and treatment process is digitized, implicit pathogenesis can be mined based on implicit meaning analysis on symptoms in the medical case and corresponding Chinese herbal medicine prescriptions, and the relation between the implicit pathogenesis and the symptoms and the relation between the implicit pathogenesis and medicine are found.

Description

Technical field [0001] The invention relates to the field of data mining, in particular to a multi-content implicit Dirichlet distribution model and a construction method thereof, and a method for mining hidden pathologies based on Chinese medical records using the model. Background technique [0002] Text mining refers to the process of extracting previously unknown, understandable, and finally available knowledge from a large amount of unstructured text data. It can be regarded as a database-based data mining and knowledge discovery process. The steps of text mining are preprocessing of input text, feature information extraction, final evaluation and result output. Text mining covers multiple disciplines, including text analysis, statistics, database technology, machine learning and other technologies. At present, text mining is widely used in medicine, business, science and engineering. In particular, text clustering techniques, such as K-means method, have been used in tradi...

Claims

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Application Information

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IPC IPC(8): G16H50/70G16H70/20
CPCG16H50/70G16H70/20
Inventor 王晓玲张颖
Owner EAST CHINA NORMAL UNIV
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