ABSTRACT
Objective To discuss the use of knowledge graph technology to connect various trivial and fragmented knowledge in various medical information systems and support comprehensive knowledge retrieval and intelligent medical applications such as Q & A and clinical decision support.Methods Based on the construction of medical field ontology and semantic labeling of medical knowledge base,the medical knowledge graph was constructed and applied to intelligent medicine,with chronic disease taken as an example.Results The construction method of medical knowledge graph and its application in semantic analysis,reasoning and disease-assisted diagnosis system based on medical knowledge base were put forward.Conclusion The application of intelligent medicine based on knowledge graph will play an important role in contradiction between the supply of high-quality medical resources and increasing medical requirements.
ABSTRACT
Objective To cxplore the research and application of big data mining technology in clinical healthcare environment.Methods The characteristics of clinical heahhcare data mining methods were expounded and the current research status of healthcare data mining technology was analyzed in clinical task according to the literature mining.Meanwhile,the application of healthcare data mining in clinical environment was introduced from the following four aspects:medicine research,personalized diagnosis,risk prediction and process mining.Results The necessity and importance of research and application of clinical healthcare data mining were illustrated.Moreover,the achicvements of healthcare data mining in clinical application,as well as existing problems and technical difficulties were summarized.Furthermore,the development tendencies of healthcare data mining were predicted.Conclusion The research and application of clinical healthcare data mining have improved the healthcare quality and promoted the medical advances,which is the developmcnt direction of clinical healthcare research.