Multi-layered elite character method for mining special medical history diagnosis rules of traditional Chinese medicine

Abstract

The invention discloses a multi-layered elite character method for mining special medical history diagnosis rules of the traditional Chinese medicine. The multi-layered elite character method comprises the following steps of designing the concentration selection probability of elite character sub-groups; distributing attributes of medical histories of the traditional Chinese medicine into 'common-elite' character groups with different classes; performing pretreatment on related attributes and correlative dependence attributes in the special medical histories of the traditional Chinese medicine; establishing a dynamic balancing strategy based on multi-layered elite characters; selecting an elite subset vector with the global search and local refining maximum optimal capability from the multi-layered elite characters; and establishing a maximum elite optimizing array to quickly mine the special medical history diagnosis rules of the traditional Chinese medicine. By the multi-layered elite character method for mining the special medical history diagnosis rules of the traditional Chinese medicine, problems of attribute fuzzy, attribute correlation and correlative dependence of special electronic medical records of the traditional Chinese medicine can be solved well, the diagnosis rule mining efficiency is improved effectively, and the robustness and the practicality are high.

Description

Technical field: [0001] The invention relates to the field of intelligent processing of TCM information, in particular to a multi-layer elite role method for excavating diagnostic rules of special TCM medical records. Background technique: [0002] As a unique cultural and scientific heritage of the Chinese nation, traditional Chinese medicine has made great contributions to the world. TCM diagnosis is mainly based on the patient's symptoms through the process of "look, smell, ask, and feel". Due to the intricate intersection of TCM syndrome types and symptoms, it is difficult to rely on computer systems for accurate TCM syndrome differentiation and treatment. However, the TCM medical record system stores Collecting a large amount of useful information, extracting the important diagnostic rules of TCM, and carrying out the classification and rule mining of TCM diseases is of great significance and value to improve the diagnosis outcome and outcome analysis of TCM diseases. ...

AI Technical Summary

Problems solved by technology

[0003] Due to the ambiguity and uncertainty of TCM medical records and the existence of a large number of redundant medical record attributes in the TCM medical record database, it is difficult to establish an intelligent auxiliary diagnosis system for TCM medical records to mine disease rules.

Especially for some special medical records of traditional Chinese medicine, there are complex correlations and interdependencies among their attributes. It is difficult to dig out the really useful diagnostic rules by using the general rule mining method to preprocess and classify medical records of traditional Chinese medicine.

In addition, general rule mining methods are often unable to deal with the multi-dimensional and complex inline relationships between special TCM medical record attributes, and cannot guarantee that the final extracted TCM medical record diagnosis rules are the optimal rule feature set for the target. Auxiliary use during diagnosis will interfere with their normal judgment of symptoms, and may lead to misdiagnosis in severe cases

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