Decision supporting frame to estimate chronic exposure suspicion to VOC chemicals using mixed statistical model
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kang, Byeong-Chul | - |
dc.contributor.author | An, Yu-Ri | - |
dc.contributor.author | Kang, Yeon-Kyung | - |
dc.contributor.author | Shin, Ga-Hee | - |
dc.contributor.author | Kim, Seung-Jun | - |
dc.contributor.author | Hwang, Seong-Yong | - |
dc.contributor.author | Nam, Suk-Woo | - |
dc.contributor.author | Ryu, Jae-Chun | - |
dc.contributor.author | Park, Jun-Hyung | - |
dc.date.accessioned | 2021-06-23T03:45:02Z | - |
dc.date.available | 2021-06-23T03:45:02Z | - |
dc.date.created | 2021-01-21 | - |
dc.date.issued | 2013-03 | - |
dc.identifier.issn | 1738-642X | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/28480 | - |
dc.description.abstract | In this paper, we examine the model for a chemical exposure decision support algorithm. Our purpose is to suggest the model frame to describe possibility of exposure with low-dose VOC chemicals for long time under normal circumstances at working place. Forensic rhetoric terms, non-exclusion exposure suspicion (NES) and exclusion exposure suspicion (EES), were defined and various statistical methods were combined basis of Bayesian approach. Decision-tree (DT) methods of linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and naive Bayes model were evaluated to classify 3 VOCs (toluene, xylene, and ehtybenzene) by means of the results of urinary test, gene expression and methylation expression experiments. Overall procedure is conducted by leave-one-out cross-validation that error rate of NES resulted in 11%. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | 대한독성 유전단백체 학회 | - |
dc.title | Decision supporting frame to estimate chronic exposure suspicion to VOC chemicals using mixed statistical model | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Hwang, Seong-Yong | - |
dc.identifier.doi | 10.1007/s13273-013-0011-6 | - |
dc.identifier.scopusid | 2-s2.0-84875834250 | - |
dc.identifier.wosid | 000317532500011 | - |
dc.identifier.bibliographicCitation | Molecular & Cellular Toxicology, v.9, no.1, pp.75 - 83 | - |
dc.relation.isPartOf | Molecular & Cellular Toxicology | - |
dc.citation.title | Molecular & Cellular Toxicology | - |
dc.citation.volume | 9 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 75 | - |
dc.citation.endPage | 83 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
dc.relation.journalResearchArea | Biochemistry & Molecular Biology | - |
dc.relation.journalResearchArea | Toxicology | - |
dc.relation.journalWebOfScienceCategory | Biochemistry & Molecular Biology | - |
dc.relation.journalWebOfScienceCategory | Toxicology | - |
dc.subject.keywordPlus | ethylbenzene | - |
dc.subject.keywordPlus | toluene | - |
dc.subject.keywordPlus | xylene | - |
dc.subject.keywordAuthor | Decision supporting system | - |
dc.subject.keywordAuthor | Discriminant analysis | - |
dc.subject.keywordAuthor | VOC | - |
dc.subject.keywordAuthor | Cross-validation | - |
dc.identifier.url | https://link.springer.com/article/10.1007/s13273-013-0011-6 | - |
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