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

Molecular & Cellular Toxicology

Byeong-Chul Kang⁵  Seong-Yong Hwang²  Ga-Hee Shin⁵  Seung-Jun Kim¹  Suk-Woo Nam³  Jae-Chun Ryu⁴  Yu-Ri An²  Jun-Hyung Park⁵  Yeon-Kyung Kang⁵ 

[1] GenoCheck Co. Ltd.$$;Hanyang University$$;Catholic University of Korea$$;Korea Institute of Science and Technology$$;Insilicogen Inc.$$

关键词: Cross-validation;   

DOI  :  10.1007/s13273-013-0011-6

学科分类：分子生物学，细胞生物学和基因

来源: Korean Society of Toxicogenomics and Toxicoproteomics

【 摘 要 】

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 naïve 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%.

【 授权许可】

Unknown