A Multi-layer Elite Role Method for Mining Diagnostic Rules of TCM Medical Records

Abstract

The invention discloses a multi-layer elite role method for excavating diagnostic rules of special TCM medical records. The method firstly designs elite role subpopulation density selection probabilities and assigns TCM medical record attributes to different types of "ordinary-elite" role populations. Carry out preprocessing of correlation and interdependence attributes in special TCM medical records; then construct a dynamic equilibrium strategy based on multi-layer elite roles, and form multi-layer elite roles by dynamically moving in and out of different elite role populations in each pentagonal evolution area Global equilibrium point; finally, the elite subset vector with the strongest global search and local refinement capabilities is selected from the multi-layer elite roles, and the strongest elite optimization array is constructed to realize the rapid mining of special TCM medical record diagnosis rules. The invention can better overcome the problems of fuzzy attributes, attribute correlation and interdependence of special TCM electronic medical records, effectively improve the mining efficiency of its diagnostic rules, and has strong robustness and practicability.

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 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. [0003]...

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 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 among 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. Sometimes supplementary use will interfere with their normal diagnosis of symptoms, and may lead to misdiagnosis in severe cases

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