ReviewIntegrated environmental assessment and management2021
Bayesian Networks in Environmental Risk Assessment: A Review.
Review in Integrated environmental assessment and management, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
29 citing papers in PubMed.
- Quantitative risk assessment of avian influenza: A scoping review.Infectious Disease Modelling · 2026Review
- Towards Bayesian-based quantitative adverse outcome pathways using in vitro data from open literature and continuous variables: a case example for liver fibrosis.Toxicological sciences : an official journal of the Society of Toxicology · 2026Article
- Unraveling land-use carbon-pollution co-evolution: A dynamic coordination framework with causal pathways and spatial zoning.iScience · 2026Article
- Advancing the Discovery of Emerging Contaminants: A Leap in Technology and Data.Environmental science & technology · 2026Review
- A Bayesian neural ordinary differential equations framework to study the effects of chemical mixtures on survival.PLoS computational biology · 2025Article
- General framework of nonlinear factor interactions using bayesian networks for risk analysis applied to road safety and public health.Scientific reports · 2025Article
- A hybrid approach combining Bayesian networks and logistic regression for enhancing risk assessment.Scientific reports · 2025Article
- Pollution is ubiquitous: Community-based quantitative human health risk assessment of metal(loid) exposure from contaminated garden plants and soils.Ecotoxicology and environmental safety · 2025Article
- Assessing mercury exposure to water and fish of the Mackenzie watershed using a Bayesian network analysis.Integrated environmental assessment and management · 2025Article
- Probabilistic ecological risk assessment for deep-sea mining: A Bayesian network for Chatham Rise, Pacific Ocean.Ecological applications : a publication of the Ecological Society of America · 2025Article
- Key challenges and developments in wildlife ecological risk assessment: Problem formulation.Integrated environmental assessment and management · 2024Review
- Elicitation of Rank Correlations with Probabilities of Concordance: Method and Application to Building Management.Entropy (Basel, Switzerland) · 2024Article
- Integrating climate model projections into environmental risk assessment: A probabilistic modeling approach.Integrated environmental assessment and management · 2024Article
- Providing an approach to analyze the risk of central oxygen tanks in hospitals during the COVID-19 pandemic.Heliyon · 2023Article
- Accuracies of various types of spinal robot in robot-assisted pedicle screw insertion: a Bayesian network meta-analysis.Journal of orthopaedic surgery and research · 2023Article
- Critical gaps in nanoplastics research and their connection to risk assessment.Frontiers in toxicology · 2023Review
- A Risk Treatment Strategy Model for Oil Pipeline Accidents Based on a Bayesian Decision Network Model.International journal of environmental research and public health · 2022Article
- Bayesian dynamic profiling and optimization of important ranked energy from gray level co-occurrence (GLCM) features for empirical analysis of brain MRI.Scientific reports · 2022Article
- Bayesian Network Applications for Sustainable Holistic Water Resources Management: Modeling Opportunities for South Africa.Risk analysis : an official publication of the Society for Risk Analysis · 2022Article
- A Bayesian Modelling Framework for Integration of Ecosystem Services into Freshwater Resources Management.Environmental management · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Human activities both depend upon and have consequences on the environment. Environmental risk assessment (ERA) is a process of estimating the probability and consequences of the adverse effects of human activities and other stressors on the environment. Bayesian networks (BNs) can synthesize different types of knowledge and explicitly account for the probabilities of different scenarios, therefore offering a useful tool for ERA. Their use in formal ERA practice has not been evaluated, however, despite their increasing popularity in environmental modeling. This paper reviews the use of BNs in ERA based on peer-reviewed publications. Following a systematic mapping protocol, we identified studies in which BNs have been used in an environmental risk context and evaluated the scope, technical aspects, and use of the models and their results. The review shows that BNs have been applied in ERA, particularly in recent years, and that there is room to develop both the model implementation and participatory modeling practices. Based on this review and the authors' experience, we outline general guidelines and development ideas for using BNs in ERA. Integr Environ Assess Manag 2021;17:62-78. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.