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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