DocumentCode
3461822
Title
Data Mining Technology for Applying of RFID and Health Examination
Author
Ben-Chang Shia ; Yi-Ting Ding ; Ya-Wun Jheng ; Ting-Wei Chang
Author_Institution
Grad. Inst. of Appl. Stat., Fu-Jen Catholic Univ., Sinjhuang, Taiwan
fYear
2009
fDate
June 30 2009-July 2 2009
Firstpage
892
Lastpage
895
Abstract
Radio frequency identification (RFID) is kind of automatic wireless recognition sum according to the gain technology, its special capability of data chasing and data collecting can load messages directly to the database and deal with many labels at one time. RFID has been applied in many domains, including medical application, like medical record system. The major of this study is medical application, this study expects RFID can combine with the data of health examination, and sort the health conditions, so that doctors and medical advisers can provide the medical information or ways of health case immediately. The purpose of this study is to classify the data of health examination we got by data mining and RFIDpsilas special capability of chasing and collecting. This study expects that we can classify the health condition of participants of health examination by the data of health examination into three classes (high risk, median risk, low risk), and provide different medical service to people by different classes.
Keywords
data mining; health care; pattern recognition; radiofrequency identification; RFID application; automatic wireless recognition; data chasing feature; data collecting feature; data mining technology; gain technology; health case medical information; health examination; high risk; low risk; median risk; medical record system; Biomedical equipment; Cervical cancer; Data mining; Databases; Diseases; Hospitals; Medical services; Radiofrequency identification; Statistics; Temperature measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
New Trends in Information and Service Science, 2009. NISS '09. International Conference on
Conference_Location
Beijing
Print_ISBN
978-0-7695-3687-3
Type
conf
DOI
10.1109/NISS.2009.236
Filename
5260784
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