Traditional Chinese medicine diagnosis and treatment knowledge graph automatic construction method based on deep learning

Abstract

The invention discloses a traditional Chinese medicine diagnosis and treatment knowledge graph automatic construction method based on deep learning. The traditional Chinese medicine diagnosis and treatment knowledge graph automatic construction method comprises the steps: constructing an initialized literature medical record corpus, carrying out sentence segmentation and word segmentation on a medical record, and marking a theory-law-prescription-medicine entity in the medical record; predicting the entity through a bidirectional LSTM, and automatically extracting the entity from traditional Chinese medicine literature medical records through a deep learning model; and clustering similar entities appearing in the same medical record to form an entity group, then forming a triple accordingto a predefined relationship between entities, and constructing a knowledge graph. According to the invention, the relationship between traditional Chinese medicine diagnosis and treatment concepts ispredefined; construction of the knowledge graph is converted into a traditional Chinese medicine diagnosis and treatment named entity recognition task; and entities are automatically extracted from traditional Chinese medicine literature medical records through a deep learning model, and the entities are clustered to form an entity set, so that the many-to-many problem between traditional Chinesemedicine diagnosis and treatment concepts is solved, and the famous and old traditional Chinese medicine diagnosis and treatment thought in the medical records is completely displayed.

Description

technical field [0001] The present invention relates to a method for automatically constructing a TCM diagnosis and treatment knowledge map, in particular to an automatic construction method for a TCM diagnosis and treatment knowledge map based on deep learning. Background technique [0002] The knowledge map is a giant, networked knowledge system built on the framework of the "semantic network", which aims to describe the concepts, entities, events and the relationship between them in the objective world. Among them, concept refers to the conceptual representation of objective things formed by people in the process of understanding the world, such as people, animals, organizations, etc. Entities are specific things in the objective world, such as basketball player Yao Ming, Internet company Tencent, etc. Events are the activities of objective events, such as earthquakes, buying and selling behaviors, etc. Relationships describe the objective relationships between concepts...

AI Technical Summary

Problems solved by technology

[0004] "Chinese Medicine Language System (TCMLS)" is mainly based on the existing structured data for the construction of knowledge graphs, while knowledge carriers such as TCM literature and books are unstructured texts, TCMLS cannot use free text (narrative language) for knowledge graphs The automatic construction and expansion of TCMLS; the knowledge map formed by TCMLS is expressed as , while in the theory of TCM diagnosis and treatment, there is a many-to-many relationship between concepts, such as syndromes and symptoms, and the form of expression should be , so TCMLS cannot fully display the theory of TCM diagnosis and treatment

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