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KMID : 1034820130090010075
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Molecular & Cellular Toxicology
2013 Volume.9 No. 1 p.75 ~ p.83
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Decision supporting frame to estimate chronic exposure suspicion to VOC chemicals using mixed statistical model
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Kang Byeong-Chul
An Yu-Ri
Kang Yeon-Kyung
Shin Ga-Hee
Kim Seung-Jun
Hwang Seong-Yong
Nam Suk-Woo
Ryu Jae-Chun
Park Jun-Hyung
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Abstract
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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. Decisiontree (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%.
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KEYWORD
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Decision supporting system, Discriminant analysis, VOC, Cross-validation
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