title: Results on mining NHANES data: a case study in evidence-based medicine.
abstract: The National Health and Nutrition Examination Survey (NHANES), administered annually by the National Center for Health Statistics, is designed to assess the general health and nutritional status of adults and children in the United States. Given to several thousands of individuals, the extent of this survey is very broad, covering demographic, laboratory and examination information, as well as responses to a fairly comprehensive health questionnaire. In this paper, we adapt and extend association rule mining and clustering algorithms to extract useful knowledge regarding diabetes and high blood pressure from the 1999-2008 survey results, thus demonstrating how data mining techniques may be used to support evidence-based medicine.
authors.affiliation: Korea Institute of Science and Technology, Biomedical Research Institute, Center for Bionics, Seoul 136-791, Republic of Korea. p3man4@gmail.com.
authors.forename: Jun won
authors.initials: Jw
authors.lastname: Lee
authors.forename: Christophe
authors.initials: C
authors.lastname: Giraud-Carrier
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D057225:Data Mining / Q000379:methods*; D019317:Evidence-Based Medicine; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D008875:Middle Aged; D009749:Nutrition Surveys; D012044:Regression Analysis