The Design And Implementation Of Ontology Knowledge For Diabetes Aided Diagnosis And Treatment System

Recently,the application of ontology in the field of medicine has become a research hotspot.Ontology is an essential part of current information resources,can accurately describe the meaning of the concept and its relationship,have strong ability in semantic expression and knowledge sharing and can provide a precise definition of consensus.In order to provide a reliable diagnosis as well therapy,the semantic interoperability of clinical information and patients' data,which currently exist across a number different of medical systems is necessary.Therefore,knowledge-based ontology system is one of favorable option for monitoring diabetes patients.The main limitations of existing,ontology-based methods for diagnosing diabetes are that they not only have semantic inconsistencies but also they have not provided a complete,clinical approach due to consideration of a few numbers of classes in their models.In this study,a knowledge-based ontology framework is developed based on the top-level ontology construction method,and ontology reuse technology for screening and treating diabetic patients.The proposed method provides a complete semantic and clinical approach by adding more detailed analysis of patients based on a standard ontology.The detailed information applied in developed framework includes symptoms,drugs,exercise,genetics,disease,complications,physical examination,laboratory tests,and other related factors.The developed ontology is implemented on Web Ontology Language(OWL),which is a semantic-web language;it enables us to create a knowledge-based representation of diabetic patients by applying different parameters.The developed framework constructs a general,not only easy to expand the knowledge-based ontology but also provides the knowledge foundation for the related domain ontology mapping.It includes the transformation of English ontology into Chinese ontology facilitates the multilingual information service,such as cross-language retrieval and machine translation,and solves the problem of two semantics and semantic inconsistency of electronicmedical records by ontology modeling.In this study,by using the pellet inference engine to realize the diagnostic reasoning of diabetes mellitus,the diabetes aided diagnosis and treatment system is developed based on the diabetes ontology.The developed Library can track the patient's electronic medical record,provide high-risk population screening,recommend personalized medication for the patient's condition,and give reasonable exercise and dietary advice to diabetic patients.This papercombines the experience accumulated by experts for many years and related knowledge in the field of diabetes,provide a general and extensible ontology knowledge base for diabetes to unsolved problems related to the existing knowledge-based ontology model for diabetes.