Research And Application Of Construction Method Of Asthma Knowledge Graph

Knowledge engineering has become an important branch of artificial intelligence,and knowledge graph,as a successful application of knowledge engineering in the big data environment,has become one of the core driving forces to promote the development of Internet and artificial intelligence.In recent years,knowledge graph construction and application technology have made rapid development.Asthma is a common chronic airway inflammatory disease,which has a long course,widespread prevalence,many influencing factors and is very complex.Therefore,it is necessary to use knowledge graph and clinical decision support system to make new energizing of asthma diagnosis and treatment activities.To build knowledge graph and asthma disease clinical decision support system can carry on the auxiliary medical decision auxiliary medical workers,according to a specific clinical problem,driven by the knowledge,give full consideration to the patient's personal specific information and gives a precise diagnosis and treatment plan,improve medical efficiency,improve service quality,reduce the medical cost,is ultimately benefit patients.This paper focuses on the difficulties and challenges in knowledge graph and clinical decision support for asthma.The work of this paper includes:Aiming at the problem of expert dependence in the generation of knowledge map of asthma,a method of building ontology based on disease prevention guidelines and extracting examples based on drug instructions was proposed.This method uses the knowledge of disease prevention and control summarized and practiced by domain experts,combines with the consensus of experts,and takes disease diagnosis and treatment as the guidance to construct the domain ontology.And based on the domain ontology,the drug instance information is extracted.In the extraction process,the method of deep learning is used to realize accurate and efficient semi-automatic instance extraction.In order to solve the problem of the interoperability of clinical decision support system,a clinical decision support model based on semantic interoperability is proposed,which uses the four-step method of "knowledge discovery-knowledge expression-knowledge application-knowledge assessment" for knowledge modeling.The interoperability between clinical decision support system and hospital electronic medical record information system is realized.