HExpPredict: in vivo exposure prediction of human blood exposome using a random forest model and its application in chemical risk prioritization

• Main Authors: Zhao, Fanrong, Li, Li, Lin, Penghui, Chen, Yue, Xing, Shipei, Du, Huili, Wang, Zheng, Yang, Junjie, Huan, Tao, Long, Cheng, Zhang, Limao, Wang, Bin, Fang, Mingliang
• Other Authors: Lee Kong Chian School of Medicine (LKCMedicine)
• Format: Article
• Language: English
• Published: 2023
• Subjects: Science::Medicine; Engineering::Computer science and engineering; Artificial Neural Network; Bioassay
• Online Access: https://hdl.handle.net/10356/169955
• Institution: Nanyang Technological University

BACKGROUND: Due to many substances in the human exposome, there is a dearth of exposure and toxicity information available to assess potential health risks. Quantification of all trace organics in the biological fluids seems impossible and costly, regardless of the high individual exposure variabili...