2020
DOI: 10.1016/j.envsoft.2020.104655
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Development of a hybrid Bayesian network model for predicting acute fish toxicity using multiple lines of evidence

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Cited by 21 publications
(23 citation statements)
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“…Bayesian network Cross-linked iron oxide (CLIO) NPs Cell-specific targeting [33,34] Small molecules and NPs NanomaterialÀQSAR (NanoÀQSAR) [34,35] Organic, inorganic, and carbon-based NPs 24 h postfertilization (hpf ) effect on zebrafish model [36,37] CORAL All categories of nanomaterial cytotoxicity modeling External leave-one-out cross-validation (LOO) for approach verification [38] Random forest (RF) Soil NPs pH Nanotoxicology prediction in ago-ecosystems [39] Linear regression (LR) Sizes of the anatase TiO 2 NPs on ROS production ROS correlations between in vitro and in vivo data [40] TiO 2 and ZnO Predictive optimization of experimental conditions [41] Organo-coated silver NPs Mechanistic ecotoxicity [41] CeO 2 NPs induce DNA damage Genotoxic dosimetry [42] Nano drug mimic Nano drug-specific protein expression [43] FeOx NPs with 108 different functionalization protocol To build the nano-QSAR model [44]…”
Section: Predictive Algorithm Nanomaterials Type Application Area In Nmentioning
confidence: 99%
“…Bayesian network Cross-linked iron oxide (CLIO) NPs Cell-specific targeting [33,34] Small molecules and NPs NanomaterialÀQSAR (NanoÀQSAR) [34,35] Organic, inorganic, and carbon-based NPs 24 h postfertilization (hpf ) effect on zebrafish model [36,37] CORAL All categories of nanomaterial cytotoxicity modeling External leave-one-out cross-validation (LOO) for approach verification [38] Random forest (RF) Soil NPs pH Nanotoxicology prediction in ago-ecosystems [39] Linear regression (LR) Sizes of the anatase TiO 2 NPs on ROS production ROS correlations between in vitro and in vivo data [40] TiO 2 and ZnO Predictive optimization of experimental conditions [41] Organo-coated silver NPs Mechanistic ecotoxicity [41] CeO 2 NPs induce DNA damage Genotoxic dosimetry [42] Nano drug mimic Nano drug-specific protein expression [43] FeOx NPs with 108 different functionalization protocol To build the nano-QSAR model [44]…”
Section: Predictive Algorithm Nanomaterials Type Application Area In Nmentioning
confidence: 99%
“…The BN nodes and arrows form a directed acyclic graph, meaning that the network can have closed loops but no cycles ( Figure 2). The nodes are usually defined by discrete states such as categories or intervals, although hybrid BNs can also contain continuous nodes (Moe et al 2020). The arrows pointing into a node in a BN represent a causal relationship that is quantified in a CPT, which relates the probability for each state of the child node to each of the states of the parents (e.g., Carriger et al 2016).…”
Section: A Brief Description Of Bayesian Networkmentioning
confidence: 99%
“…The qualitative structure of a BN can be used to capture the causal relationships in a conceptual model for ERA, whereas the quantitative part can capture uncertainties and nonlinear interactions between the conceptual model's variables (Carriger and Parker 2021). The uncertainties regarding these relationships are captured in the CPTs (Ayre and Landis 2012; Moe et al 2020). Thus, compared to the traditional use of conceptual models in ERA, BNs take the utility of the conceptual model one step further by allowing for quantitative information and incorporating the uncertainties in knowledge of causes and effects.…”
Section: Applications Of Bayesian Network To Environmental Risk Assementioning
confidence: 99%
“…This lack is likely a result of the history of using specific BN software products that are designed for discrete variables or provide only a limited selection of continuous distribution types. Several popular BN softwares nowadays accommodate hybrid networks (e.g., Hugin, Analytica, AgenaRisk, bnlearn in R), but their analytical use is still limited compared to discrete models (see, however, Moe et al 2020, for example), and requires more statistical expertise from both the modeler and the end user of the model or its results. It is also noteworthy that although conditional probability tables of discrete variables are able to accommodate and express nonlinearities, step functions, and other nonparametric functional responses between the variables, the continuous variables are often modeled using linear functions or other simple parametric functional forms.…”
Section: Discussionmentioning
confidence: 99%