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Decision supporting frame to estimate chronic exposure suspicion to VOC chemicals using mixed statistical model

Title
Decision supporting frame to estimate chronic exposure suspicion to VOC chemicals using mixed statistical model
Author
황승용
Keywords
Decision supporting system; Discriminant analysis; VOC; Cross-validation
Issue Date
2013-07
Publisher
THE KOREAN SOCIETY OF TOXICOGENOMICS AND TOXICOPRPTEOMICS
Citation
MOLECULAR & CELLULAR TOXICOLOGY, 권: 9, 호: 1, 페이지: 75-83
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%.
URI
https://link.springer.com/article/10.1007%2Fs13273-013-0011-6http://hdl.handle.net/20.500.11754/45581
ISSN
1738-642X
DOI
10.1007/s13273-013-0011-6
Appears in Collections:
GRADUATE SCHOOL[S](대학원) > BIONANOTECHNOLOGY(바이오나노학과) > Articles
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