Medical knowledge base construction method based on question-and-answer system

Abstract

The invention discloses a medical knowledge base construction method based on a question-and-answer system, and relates to a medical knowledge base. The medical knowledge base construction technology based on the question-answering system mainly includes data processing, data analysis and an expert question-and-answer platform. Firstly, entity and correlation relations are extracted from clinical data by a hierarchical partitioning method at a data processing stage. Secondly, extracted results are analyzed by an association rule algorithm, entity correlation is mined, the mined entity correlation is matched with a medical dictionary, and correctly matched results are directly stored into the knowledge base. Finally, questions are automatically generated from entity correlation which cannot be confirmed by crowd-sourcing technology, the questions are submitted to an expert question-and-answer platform for answering the questions, and final results are selected from answers of experts by a majority voting algorithm and stored into the medical knowledge base.

Description

technical field [0001] The invention relates to a medical knowledge base, in particular to a method for constructing a medical knowledge base based on a question answering system. Background technique [0002] The digitalization and informatization of the medical system is an inevitable trend in the development of medicine. With the development of information technology, the medical industry is experiencing an unprecedented information explosion. In particular, smart medical care has become one of the hot topics in smart cities. Many systems have been applied to Medical information management and retrieval. The data generated in this process, such as electronic health records and electronic medical records, urgently need a powerful information management tool for processing and analysis. [0003] The knowledge base, also known as the artificial intelligence database, is a structured, easy-to-operate, and easy-to-use organized knowledge cluster. It is not just a tool for que...

AI Technical Summary

Problems solved by technology

[0004] Existing medical knowledge bases are usually constructed using machine learning methods, but due to the obtained wrong entity relationships, the results are not satisfactory and the quality of the knowledge base cannot be improved

Moreover, the functions of existing medical knowledge bases are relatively single, and most of them only carry out simple integration of knowledge, mostly static data, the efficiency of knowledge reuse is not high, and the practical value is not high

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