The Research And Application Of Hospital Information System On Data Mining

With the development of information processing technology,the popularization of its application in in various industry sectors and the increase of generating and collection methods of data,the data quantity grown explosively.The traditional data processing method couldn’t satisfy people’s higher demands on data processing.It is difficult to find the accuracy of the concerned data from a large amount of data and also find the inner relationship between the data and the phenomena of the transaction in the Data Processing that it lead to the emergence of Data Mining technique.Nowadays the applications of data mining in the area of medicine,not only about the doctor’s auxiliary diagnosis and treatment,but also about the patient and hospital information management.The purpose of this paper is ab out the data mining technology and association rule mining technology on the basis of data from Mawangdui hospital of Hunan province,studied mainly on data mining of association rules algorithm in medical data analysis and application research,the main c ontent as follows:At First analyzed the Apriori algorithm,which is the Classic algorithms of association rules.Considered the main bottleneck in the Apriori algorithm,such as frequent item sets’ generation problems,multiple scanning in the database,etc.,and proposed an improved Apriori algorithm by reducing the number of scanning database and compressing further iterative scan with the transaction number.And then comparing the Apriori algorithm in the experimental test and comparison before and after improvement through the experiment,and analyzing the mining result.The results showed that the improved Apriori algorithm reduced the number of indifferent rules,so that it improve the efficiency and can achieve scientific and accurate mining decision-making data more better.The hospital information system are introduced,mainly about the structure and function of outpatient service subsystem,and analyzed the medical data,applied the improved algorithm to the hospital information management system and analyzed the association rule with the complications in outpatient data for data mining.It was found that it can reduce the error diagnosis probability after the application of association rules.And it could find the links in the implied condition and the onset of disease symptoms of unknown disease,assist the doctors to determine diagnostic criteria.It also could carry on the corresponding protection and protection measures to the sick person(such as high-risk groups)according to the characteristics of disease distribution,and so on.Data mining on medical image data.We proposed a more suitable for a large number of medical image data mining algorithm aiming at the deficiencies in FP-tree algorithm,which was the common mining algorithm of medical image.The improved algorithm compressed the generated frequent collection of data into more frequent pattern tree binary tree,which was used to store the correlation information of the project,the frequent set was finally generated by pattern tree.Th e improved algorithm and FP-tree algorithm help increase the efficiency of association rule mining,and the improved FP-tree algorithm was applied to mine the image of breast cancer,produced the final mining rules,and then analyzed the related causes whi ch was derived from breast cancer.It help provide a scientific basis for scientific treatment and prevention.