Medical Self-diagnosis System Based On Knowledge Graph

The rapid development of society has promoted the improvement of people’s material living standards,the situation of sedentary office,busy working overtime day and night,and the increase of age,making people pay more attention to their health.However,there are three major problems in offline medical care: First,people usually choose to go to large hospitals for testing,resulting in a run on medical resources.Second,work is too busy to have time.Third,the efficiency of search engines is low,and the huge amount of medical data greatly reduces the utility of traditional search engines.When users search for keywords,they may cause search results due to incomplete description of symptoms,advertisement recommendations of search engines,and traffic recommendations of big data.There is a big deviation.Faced with these three problems,it is necessary to design a query engine that can be searched on the Internet and uses knowledge graph technology to accurately describe diseases and symptoms.This paper designs a disease-symptom knowledge map to provide a knowledge base for medical self-diagnosis.The main contributions of this paper are as follows:1.Realize the acquisition of knowledge,the modeling and structured storage of knowledge base.This article searches for suitable information in the network,obtains information through downloading and crawling,and completes the acquisition of data.Build and improve knowledge models,identifying the types of entities and relationships needed to build a knowledge base.Finally,the medical knowledge entities and relationships obtained from the research are structured and stored by using the graph database to complete the construction of the knowledge base.2.Realize the kernel of self-diagnosis system.The system converts the knowledge graph and information provided by the user into propositional logic formulas.And through the satisfiability judgment to complete the disease screening.Contribution of symptoms to disease was calculated using the TF-IWF algorithm.The disease score is calculated based on the contribution of symptoms.The symptom scoring function is completed through different calculation schemes,and a more appropriate scoring standard is selected by comparison.3.Practical application of medical self-diagnosis systemAll the programs in this paper are not only reflected in the theoretical ideas,but also have realized the program design,which can be put into practice formally.The medical self-diagnosis system has made an effective contribution to the medical industry.It can provide preliminary consultation on physical conditions for people without medical experience,and can predict simple common diseases.Users who find minor illnesses usually go to the local community hospital,which relieves the pressure on doctors in large public hospitals to a certain extent and improves the status of medical services in society.If the medical self-diagnosis function can be put into the hospital website,the network traffic of the hospital can also be increased.