Model Aided Intelligent Medical Diagnosis System Based On The Shared Information

Along with the social science and technology developing rapidly, people’s lifelevel increasing, and material life enriching at the same time, health problems arehaving more and more people’s attention, especially the remote rural areas. Becauseof the backward technology, lacking of medical equipment and doctors resources,farmers’ health problems are getting more and more the national attention. In responseto improve rural medical conditions and response to the call of our country, allowingthe farmer brother to enjoy the modern science, technology and the modern medicalresults, is of great social and realistic significance. For this, to design a diagnosis andassist treatment for the town hospital doctors, and can be available for lack ofexperience internship learning process of intelligent diagnosis and treatment assistantdiagnosis system is very necessary.This paper argues that, reasonable and practical medical diagnosis system shouldhave the following advantages: first of all, can simulate the doctor diagnosed thepatients’ real process. Second，support and help the doctor diagnosed a doctordiagnose disease. Finally, there is the self-learning, self-summing up experienceability.How to enable effective accurately diagnosed patients’ problems? This paperputs forward the method based on the sharing information. On one hand, diagnosis,according to the medical diagnosis system physicians and patients deal with shareddatabase of disease after the conclusion of information and tips are given, throughanalysis，finally correct conclusion for patients with custom. On the other hand, thesystem through the analysis data, gives physicians hint, guide doctors judgment, inorder to decrease the misdiagnosis rate and improve the doctors professional ability.Having set up a database, we will solve the mass data storage of medicaldiagnosis, but as a large number of diagnosis of data input and the problem willfollow. Mass data far beyond what we can understand the scope, and lead to the largeamount of effective data by unused，cause data waste of resources. Data mining canbe made this problem solved. The data mining technology analysis of medicaldatabase mass data, extract useful information, the data are no longer idle, promotethe development of medical science. At present, the data mining technology has beensuccessfully applied to the medical each domain, such as medical image analysis, DNA testing, and disease prevention, physiological monitoring data analysis, obtaingood effect.For patients with pattern recognition method for auxiliary diagnose disease, itcan not only save medical experts precious time, also can let the auxiliary medicaldiagnosis system has self-learning ability. Along with the number increasing of thedata in the system of diagnosis, the system will become more and more intelligentas well as more and more perfect. At the same time, it will also raise the diagnosticaccuracy.