A new approach to a legacy concern: Evaluating machine-learned Bayesian networks to predict childhood lead exposure risk from community water systems.
Riley Mulhern,Javad Roostaei,Sara Schwetschenau,Tejas Pruthi,Chris Campbell,Jacqueline MacDonald Gibson +5 more
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In this paper, the relationship between children's blood lead levels and drinking water system characteristics using machine-learned Bayesian networks was assessed using blood lead records from 2003 to 2017 for 40,742 children in Wake County, North Carolina.About:
This article is published in Environmental Research.The article was published on 2022-03-01 and is currently open access. It has received 4 citations till now. The article focuses on the topics: Lead (geology) & Risk assessment.read more
Citations
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Journal ArticleDOI
Improved Decision Making for Water Lead Testing in U.S. Child Care Facilities Using Machine-Learned Bayesian Networks
TL;DR: In this paper , machine-learned Bayesian network (BN) models were used to predict building-wide water lead risk in over 4,000 child care facilities in North Carolina according to maximum and 90th percentile lead levels from water lead concentrations at 22,943 taps.
Journal ArticleDOI
Differential exposure to drinking water contaminants in North Carolina: Evidence from structural topic modeling and water quality data.
TL;DR: In this paper , structural topic modeling (STM) and geographic mapping is used to identify the main topics and pollutant categories being researched and the areas exposed to drinking water contaminants.
Journal ArticleDOI
Predictive modeling of indoor dust lead concentrations: Sources, risks, and benefits of intervention.
Matthew Dietrich,Cynthia F Barlow,Jane Entwistle,Diana Meza-Figueroa,Chenyin Dong,Peggy Gunkel-Grillon,Khadija Jabeen,Lindsay Bramwell,John T. Shukle,L. Wood,Ravi Naidu,Kara L. Fry,Mark Taylor,Gabriel M. Filippelli +13 more
TL;DR: In this article , a global dataset (∼40 countries, n = 1951) of community sourced household dust samples were used to predict whether indoor dust was elevated in Pb, expanding on recent work in the United States.
Journal ArticleDOI
Intelligent lung cancer MRI prediction analysis based on cluster prominence and posterior probabilities utilizing intelligent Bayesian methods on extracted gray-level co-occurrence (GLCM) features
Jing Yang,Por Lip Yee,Hanen Karamti,Elsayed Mohamed Tag Eldin,Amjad Aldweesh,Atef El Jery,Lal Hussain,Abdulfattah Omar +7 more
TL;DR: In this article, a detailed posterior probabilities analysis was conducted to unfold the network associations among the gray-level co-occurrence matrix (GLCM) features, and the cluster prominence was selected as target node.
References
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Journal ArticleDOI
Evaluating the Effects of Full and Partial Lead Service Line Replacement on Lead Levels in Drinking Water
TL;DR: Full and partial LSLR more than doubled premises plumbing lead release in the short term and did not reduce L1, L2 lead releases in the long term, and even 6 months after partial L SLR, 27% of first-draw lead levels were greater than 15 μg L(-1) (the U.S. EPA action level), compared with 13% pre-replacement.
Journal ArticleDOI
Impact of treatment on Pb release from full and partially replaced harvested Lead Service Lines (LSLs).
TL;DR: The results of this study raise questions concerning protocols based on short 30 min stagnation (as those used in Canada) due to their incapacity to consider particulate lead release generated mostly after longer stagnation.
Journal ArticleDOI
Seasonality and trend in blood lead levels of New York State children.
TL;DR: Pediatricians should be aware of the seasonality of BLLs and continue to screen children at their normally scheduled well-child visits rather than delaying until summertime and possibly postponing the discovery of an elevated BLL.
Proceedings ArticleDOI
Predictive Modeling for Public Health: Preventing Childhood Lead Poisoning
Eric Potash,Joe Brew,Alexander Loewi,Subhabrata Majumdar,Andrew Reece,Joe Walsh,Eric W. D. Rozier,Emile Jorgenson,Raed Mansour,Rayid Ghani +9 more
TL;DR: A model is built that predicts the risk of a child to being poisoned so that an intervention can take place before that happens and has the potential to have a significant impact on both health and economic outcomes for communities across the US.
Journal ArticleDOI
Weaknesses in Federal Drinking Water Regulations and Public Health Policies that Impede Lead Poisoning Prevention and Environmental Justice
KatnerAdrienne,J PieperKelsey,LambrinidouYanna,BrownKomal,HuChih-Yang,W MielkeHoward,A EdwardsMarc +6 more
TL;DR: The failure of the regulatory community to protect the residents of Flint, Michigan, from prolonged exposure to hazardous levels of lead in their drinking water has drawn public attention to long-acknowledged weaknesses in the implementation and oversight of the U.S. Environmental Protection Agency's (EPA's) Lead and Copper Rule (LCR) as discussed by the authors.
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