Diseases Association Discovery Based on XML EMR

Author

Yabin, Xu ; Hongyu, Peng

Author_Institution

Inst. of Comput., Beijing Inf. Sci. & Technol. Univ., Beijing, China

Volume

3

fYear

2010

fDate

6-7 March 2010

Firstpage

503

Lastpage

506

Abstract

First, the meaning of data mining from EMR with a view to discover valuable knowledge, as well as current problems is introduced. Then, several possible storage methods for EMR are deeply analyzed and studied. On this basis, the solution of storage XML EMR with DB2/9.5 hybrid database is presented. The XQ-Apriori algorithm based on classic Apriori algorithm and XML query language XQuery, as well as an application case for association rules mining directly from XML EMR and other kinds of XML documents is introduced in detail. It is proved the association between diseases can be discovered in effect by using this algorithm. Finally, the application circs and the application scope of the algorithm are summarized and illuminated, and further developed research work by author are recommended.

Keywords

XML; data mining; medical information systems; query languages; Apriori algorithm; DB2/9.5 hybrid database; XML EMR; XML documents; XML query language; XQ-Apriori; XQuery; association rules mining; data mining; diseases association discovery; electronic medical record; Application software; Biomedical imaging; Data mining; Diseases; Educational technology; Medical diagnostic imaging; Medical treatment; Relational databases; Standards organizations; XML; Data Mining; Disease Association Discovery; EMR; XML; XQuery;

fLanguage

English

Publisher

ieee

Conference_Titel

Education Technology and Computer Science (ETCS), 2010 Second International Workshop on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-6388-6

Electronic_ISBN

978-1-4244-6389-3

Type

conf

DOI

10.1109/ETCS.2010.501

Filename

5458595