Hazard Screening Methods for Nanomaterials: A Comparative Study.

ABSTRACT: Hazard identification is the key step in risk assessment and management of manufactured nanomaterials (NM). However, the rapid commercialisation of nano-enabled products continues to out-pace the development of a prudent risk management mechanism that is widely accepted by the scientific community and enforced by regulators. However, a growing body of academic literature is developing promising quantitative methods. Two approaches have gained significant currency. Bayesian networks (BN) are a probabilistic, machine learning approach while the weight of evidence (WoE) statistical framework is based on expert elicitation. This comparative study investigates the efficacy of quantitative WoE and Bayesian methodologies in ranking the potential hazard of metal and metal-oxide NMs-TiO₂, Ag, and Z

SUBMITTER: Sheehan B 

PROVIDER: S-EPMC5877510 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature