Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Jun Won | - |
dc.contributor.author | Giraud-Carrier, Christophe | - |
dc.date.accessioned | 2024-01-20T12:04:19Z | - |
dc.date.available | 2024-01-20T12:04:19Z | - |
dc.date.created | 2022-01-25 | - |
dc.date.issued | 2013-06 | - |
dc.identifier.issn | 0010-4825 | - |
dc.identifier.uri | https://pubs.kist.re.kr/handle/201004/127986 | - |
dc.description.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. (C) 2013 Elsevier Ltd. All rights reserved. | - |
dc.language | English | - |
dc.publisher | PERGAMON-ELSEVIER SCIENCE LTD | - |
dc.title | Results on mining NHANES data: A case study in evidence-based medicine | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.compbiomed.2013.02.018 | - |
dc.description.journalClass | 1 | - |
dc.identifier.bibliographicCitation | COMPUTERS IN BIOLOGY AND MEDICINE, v.43, no.5, pp.493 - 503 | - |
dc.citation.title | COMPUTERS IN BIOLOGY AND MEDICINE | - |
dc.citation.volume | 43 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 493 | - |
dc.citation.endPage | 503 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.identifier.wosid | 000318320700011 | - |
dc.identifier.scopusid | 2-s2.0-84875916799 | - |
dc.relation.journalWebOfScienceCategory | Biology | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Engineering, Biomedical | - |
dc.relation.journalWebOfScienceCategory | Mathematical & Computational Biology | - |
dc.relation.journalResearchArea | Life Sciences & Biomedicine - Other Topics | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Mathematical & Computational Biology | - |
dc.type.docType | Article | - |
dc.subject.keywordPlus | ASSOCIATION RULES | - |
dc.subject.keywordPlus | DISCOVERY | - |
dc.subject.keywordPlus | DATABASES | - |
dc.subject.keywordAuthor | Medical data mining | - |
dc.subject.keywordAuthor | Observational study | - |
dc.subject.keywordAuthor | Evidence-based medicine | - |
dc.subject.keywordAuthor | NHANES | - |
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