Traditional Chinese medicine data processing method and system based on constrained concept lattice of attribute

Abstract

The present invention provides a traditional Chinese medicine data processing method and system based on the constrained concept lattice of the attribute. The method comprises: obtaining to-be-diagnosed medical record data and a similarity degree model pre-constructed based on the concept lattice structure of the attribute, wherein the similarity degree model is established based on the traditional Chinese medicine data; carrying out Chinese word segmentation and part-of-speech annotation on the attributes corresponding to the syndromes in the to-be-diagnosed medical record data so as to obtain the single-valued background; through multiple different constraints in the construction manner based on the concept lattice structure of the attribute, processing the attributes in the single-valued background, so as to form the constrained concept lattice; and comparing attribute nodes in the constrained concept lattice with the attribute nodes in the similarity degree model, so as to obtain a syndrome type. According to the method and system provided by the present invention, each attribute node in the similarity degree model is matched with the attribute node in the constrained concept lattice, and a diagnosis result is finally obtained, so that node matching accuracy is improved, matching time is reduced, and user experience is improved.

Description

technical field [0001] The invention relates to the field of TCM data processing, in particular to a TCM data processing method and system based on an attribute-based constraint concept lattice. Background technique [0002] The application of computers has penetrated into every corner of social progress and human life, but the application of computers in the medical field is still mainly in the stage of electronic data processing and medical information management, such as computer-assisted teaching, hospital financial management systems, electronic medical records, etc. . The intelligent auxiliary diagnosis and treatment system put into practical use is only in the research and development stage. [0003] Medical diagnosis is a process of deriving the cause of disease based on the patient's medical history, symptoms and other information. Reasoning is an important step in the diagnostic process. In the process of experts diagnosing patients, experts mainly rely on their...

AI Technical Summary

Problems solved by technology

Medical experts are often unable to quantitatively describe how they arrived at the diagnosis, which means that it is difficult to build an accurate model

It is also difficult for a computer to simulate an expert's diagnostic method to diagnose a patient's condition

[0004] In the prior art, based on knowledge, the constrained concept lattice is used to represent and process specific medical cases. Its biggest advantage lies in the dynamic knowledge base, that is, the case base is continuously increased through incremental learning, and the existing constrained concept lattice is Based on the object-based progressive structure, since the medical record data to be diagnosed contains a large number of objects, matching each object with the constraint conditions requires a large amount of calculation and a long matching time, and then generates the final diagnosis syndrome time course, which affects the user experience.

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