The Research And Design Of Chronic Kidney Disease Classification Prediction

Along with the development of computer, application of human intelligence in all fields,expert assistant diagnosis system has been through over50years, people’s understanding andtreatment requirements toward disease diagnosis is becoming deeper and higher. In recentyears, application of artificial neural networks in medicine is attracting more and moreattention. The chronic nephropathy grading predict aided diagnosis system is mostly based onthe study of GFR prediction BP neural network model in prophase. This system can be usedto record, analyze and estimate the individual’s development of disease, it can also supplyonline consultation and diagnosis advices. The system helps to improve traditional kidneydisease treatment mode, realize hierarchical effective treatment and expert resources sharingof kidney disease. This article design an expert system based on this ideology, both averageuser and doctors can make use of this system. Average users can get information on patientscondition, Therapeutic effect evaluation and some other services like online consultation withthis system. The system can supply functions like data collection, data processing, doctorconsultation and classification of chronic kidney disease and its develop prediction. In thisway, the system can help more patients to receive treatment initiatively and doctors to maketreatment plan.Chronic nephropathy grading predict aided diagnosis system, its main service objectincludes healthy people, doctors, patients with chronic kidney disease and so on. Doctors usemedical devices to monitor physiological parameters, the data is transformed remotelythrough TCP/IP communication protocol and processed on PCs of doctors with this system,then the case history will be established, analyzed and stored. The user’s information will bestored in central database server and user profile will be established. The system will get GFRestimate figure from GFR estimation model realized by C++based on users’ monitoring data,then the system will call knowledge base and inference device in expert system, andcomprehensively analyze the patient condition, give out the diagnosis classification result andtreatment advice at last. Doctors can estimate health condition of patient throughcommunication, then give out effectiveness estimation of current treatment plan and furthertreatment advice. This system use the diagnosis result and expert case history as base, GFRestimation as method, expert knowledge as center, the design is mainly for chronicnephropathy grading predict aided diagnosis system has humane, intelligent and integrated asfeatures.Users can consult a suitable doctor according to their own condition, doctors can give treatment advices based on users’ case history description, active description, monitoring dataand other health information, so both the patients and doctors can get more targeted andeffective service. Doctors can manage users’ treatment information and daily life information,and when the ordinary client is loading, the system will call treatment information and show itto the user with chart, thus, make the service more humane and the system more functional.This article deeply discusses doctor client, ordinary client, development process of serverapplications and relative technology, according to the system functional requirements, thesystem use C/S service architecture, use C++to program on Qt platform, use MYSQLdatabase technology to accomplish the database development.