Research On Hypertension Diagnosis And Treatment System Based On Ontology And CBR

Hypertension seriously affects the health of our residents, but at present our country’s medical and health conditions can not keep up with the demand of hypertension patients. Such problems as "difficulty and high cost of the doctor" still exist. As a result, the state vigorously promotes the medical information construction, so as to improve the awareness, treatment and control of high blood pressure. It is very realistic that how to use artificial intelligence and other areas of computer information technology to tackle the problems and how to lead information construction in medicine more quickly through rapid development of information.As a new field of artificial intelligence, Semantic Web makes computer has a certain judgment and thinking ability of the intelligent network. Ontology, as the core concept in the semantic web, is a description of the essence and the details of standard concept. Case-based Reasoning is a kind of technology using past experience to solve the current problems, which is closer to doctors’ medical decision-making in reality and process of pathological diagnosis. In this paper, it has important research value to combine case-based reasoning and semantic web technology in diagnosis and treatment of high blood pressure. At first, this paper integrates the pathogenesis and treatment of hypertension pathology knowledge, extracts related medical concept, diagnosis index and method of treatment, then uses Stanford University Ontology to build software, Protege, to establish hypertension domain Ontology model. Second, it uses Jena Ontology Subsystem, API inference Subsystem inference Subsystem and the established hypertension domain Ontology model category to write a Java program to create hospitalized patients Ontology as an example. Based on the Jena grammar rules to write the two inference rules of the diagnosis and treatment of high blood pressure, it imports case-based reasoning in the system, extracts partial Ontology instances as small case base, designs the case structure database by using the XML format and searches the case based on case matching similarity algorithm. Then, according to the demand of the system to combine the case-based reasoning with the rules of Ontology reasoning technology, it designs the logic management inquiry of ontology and its knowledge database. At last, through theoretical analysis and specific techniques, it designs a B/S framework to assist diagnosis and treatment of hypertension combining with the advantage of Ontology, rule-based reasoning (RBR) and Case Based Reasoning.Around this frame work structure, it uses the struts framework programming system to carry out the key link for the experimental implementation.At present, this system still has many shortcomings and needs to improve and enhance gradually. It is also an exploration and temptation to applied Semantic Web theory to practice. I hope it can provide example and a way of related Web3.0application development for subsequent researchers.