A Hybrid Bayesian Network Framework for Risk Assessment of Arsenic Exposure and Adverse Reproductive Outcomes

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dc.authoridOrak, Nur Hanife/0000-0002-3830-9260
dc.authorwosidOrak, Nur H./ABI-4391-2020
dc.authorwosidOrak, Nur Hanife/L-9971-2019
dc.contributor.authorOrak, Nur H.
dc.date.accessioned2021-12-01T18:47:16Z
dc.date.available2021-12-01T18:47:16Z
dc.date.issued2020
dc.department[Belirlenecek]en_US
dc.description.abstractArsenic contamination of drinking water affects more than 137 million people and has been linked to several adverse health effects. The traditional toxicological approach, dose-response graphs, are limited in their ability to unveil the relationships between potential risk factors of arsenic exposure for adverse human health outcomes, which are critically important to understanding the risk at low exposure levels of arsenic. Therefore, to provide insight on the potential interactions of different variables of the arsenic exposure network, this study characterizes the risk factors by developing a hybrid Bayesian Belief Network (BBN) model for health risk assessment. The results show that the low inorganic arsenic concentration increases the risk of low birth weight even for low gestational age scenarios. While increasing the mother's age does not increase the low birthweight risk, it affects the distribution between other categories of baby weight. For low MMA% ( < 4%) in the human body, increasing gestational age decreases the risk of having low birthweight. The proposed BBN model provides 82% sensitivity and 72% specificity in average for different states of birthweight.en_US
dc.identifier.doi10.1016/j.ecoenv.2020.110270
dc.identifier.issn0147-6513
dc.identifier.issn1090-2414
dc.identifier.pmid32036100en_US
dc.identifier.scopus2-s2.0-85079005342en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.ecoenv.2020.110270
dc.identifier.urihttps://hdl.handle.net/20.500.12684/10214
dc.identifier.volume192en_US
dc.identifier.wosWOS:000518502300047en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakPubMeden_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorOrak, Nur H.
dc.language.isoenen_US
dc.publisherAcademic Press Inc Elsevier Scienceen_US
dc.relation.ispartofEcotoxicology And Environmental Safetyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArsenic exposureen_US
dc.subjectMaternalen_US
dc.subjectLow birthweighten_US
dc.subjectBayesian networksen_US
dc.subjectRisk analysisen_US
dc.subjectBiomarkersen_US
dc.titleA Hybrid Bayesian Network Framework for Risk Assessment of Arsenic Exposure and Adverse Reproductive Outcomesen_US
dc.typeArticleen_US

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