The Application Of Data Mining Technology In The Diagnosis And Treatment Of Clinical Disease

With the rapid development of Internet technology, Medical and healthinformation is listed as an important pillar in the medical and health system "fourbeams eight columns". The new medical reform program also makes it clear thatperfecting the public Healthcare Information Platform, and the most mainly part ofthis system is disease control network, improving the prediction of early warning andanalysis reporting capability requirements. On the basis of the information platformfor the regional health agencies, in order to meet various of agencies and personnelneeds, we can build a health information integration application development as wellas day-to-day operations of the data sharing and exchange platform, and through theRegional Healthcare Information Platform, we will integrate health data whichdispersed in different medical institutions to a logical integrity information system.During this process, Regional healthcare information platform which based onelectronic medical records stored a large number of medical records data, usually wejust simple query these data, delete, modify, and other operations in the day-to-daymanagement of the process, There is no doubt that we wasted these valuable resources.With the rising and development of data mining technology, We can use data miningtechniques to carry out excavation of these medical records data, analysising the datadeeply and obtaining the data we need in our daily life.Based on the regional healthcare information platform which based on electronicmedical records, we establish the dedicated database for data mining through cleaning,integration and selection, and transformation the sharing of data in the regionalhealthcare information platform. We call it as patient illness database. Then we usethe data mining technology to carry out excavation of these medical records data. Thepaper carried out the data mining which based on summary of the rules, and obtained the relationship between the various of symptoms associated with a disease therelationship between the various symptoms in the disease. we also analyzed theresults and obtained useful knowledge. These results provide an important basis formedical workers to diagnose disease.