Traditional Chinese medicine diagnosis method and system based on k-nearest neighbor labeled specific weight characteristics

A technology with specific weights and diagnostic methods, which is applied in diagnosis, diagnostic recording/measurement, medical science, etc., and can solve the problem that data mining technology cannot perform modeling and analysis at the same time, Chinese medicine syndrome diagnosis has not achieved satisfactory results, and symptom weight is ignored And other issues

Active Publication Date: 2015-05-13
SHANGHAI UNIV OF T C M
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Problems solved by technology

However, in the clinical practice of traditional Chinese medicine, syndromes often do not appear singly, but are often intertwined. Traditional data mining technology cannot perform modeling and analysis at the sa

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  • Traditional Chinese medicine diagnosis method and system based on k-nearest neighbor labeled specific weight characteristics
  • Traditional Chinese medicine diagnosis method and system based on k-nearest neighbor labeled specific weight characteristics
  • Traditional Chinese medicine diagnosis method and system based on k-nearest neighbor labeled specific weight characteristics

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Embodiment Construction

[0020] Hereinafter, the present invention will be described in detail with reference to the drawings and examples. It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0021] figure 1 Shown is the flow chart of the TCM diagnosis method based on the specific weight feature of the k-nearest neighbor label in Embodiment 1 of the present invention, including the following steps:

[0022] Step 101: Obtain the weight information of characteristic data of cases under different categories according to the preset weight determination strategy;

[0023] The preset weight determination strategies include mutual information determination methods, information gain determination methods, random forest importance determination methods, and frequency determination methods.

[0024] The process of obtaining the weight information of feature data of cases under different categorie...

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Abstract

The invention provides a traditional Chinese medicine diagnosis method and system based on specific weight characteristics of k-nearest neighbor labels to solve the problems. The method includes the steps of acquiring characteristic data weight information of cases of different types according to a preset weight determination strategy; according to the characteristic data weight information, acquiring a weighted Euclidean distance between any two cases, and selecting the preset number of cases having the minimum weighted Euclidean distances; subjecting the selected cases to ML-LSWAKNN (multi-label learning of specific weighted adjustment k-nearest neighbor) to acquire evaluation indexes corresponding to the selected cases. The method and the system have the advantages that the influence of characteristic weighting upon classifying is fully considered, and classifying precision is greatly improved.

Description

technical field [0001] The invention belongs to the field of information processing of traditional Chinese medicine, and in particular relates to a multi-label traditional Chinese medicine syndrome diagnosis method and system based on specific weight characteristics of k-nearest neighbor labels. Background technique [0002] Syndrome differentiation and treatment are the characteristics and essence of traditional Chinese medicine. Syndrome is a summary of the overall response to pathophysiological changes of human diseases. It is the result of syndrome differentiation and the basis for treatment. The traditional method system of syndrome differentiation is rich in connotation and has experienced the test of long-term clinical practice of TCM. However, in the system of TCM syndrome differentiation method, the diagnosis of TCM syndrome is based on the intuitive method of looking, smelling, asking, and feeling. Doctors make subjective judgments, and this kind of artificial judg...

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Application Information

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IPC IPC(8): G06F19/00A61B5/00
Inventor 刘国萍颜建军徐玮斐王忆勤郑舞
Owner SHANGHAI UNIV OF T C M
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