AIMC Topic: Hazardous Substances

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Transfer learning for predicting human skin sensitizers.

Archives of toxicology Feb 26, 2019
Computational prioritization of chemicals for potential skin sensitization risks plays essential roles in the risk assessment of environmental chemicals and drug development. Given the huge number of chemicals for testing, computational methods enabl...
Humans Machine Learning Databases, Factual Animal Testing Alternatives Hazardous Substances Dermatitis, Allergic Contact Risk Assessment Skin Models, Biological
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Ontology-based semantic mapping of chemical toxicities.

Toxicology Nov 20, 2018
This study was undertaken to evaluate the use of ontology-based semantic mapping (OS-Mapping) in chemical toxicity assessment. Nineteen chemical-species phenotypic profiles (CSPPs) were constructed by ontologically annotating the toxicity responses r...
Semantics Biological Ontologies Hazardous Substances Phenotype Animals Risk Assessment Mice Humans Rats Fishes
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Comparison of Machine Learning Models for Hazardous Gas Dispersion Prediction in Field Cases.

International journal of environmental research and public health Jul 10, 2018
Dispersion prediction plays a significant role in the management and emergency response to hazardous gas emissions and accidental leaks. Compared with conventional atmospheric dispersion models, machine leaning (ML) models have both high accuracy and...
Chemical Hazard Release Normal Distribution Hazardous Substances Machine Learning Models, Theoretical Support Vector Machine Gases
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Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm.

PloS one Jun 21, 2018
Route optimization of hazardous materials transportation is one of the basic steps in ensuring the safety of hazardous materials transportation. The optimization scheme may be a security risk if road screening is not completed before the distribution...
Hazardous Substances Transportation Humans Neural Networks, Computer Algorithms
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Prediction of skin sensitization potency using machine learning approaches.

Journal of applied toxicology : JAT Jan 10, 2017
The replacement of animal use in testing for regulatory classification of skin sensitizers is a priority for US federal agencies that use data from such testing. Machine learning models that classify substances as sensitizers or non-sensitizers witho...
Hazardous Substances Dermatitis, Allergic Contact Machine Learning Skin Humans United States Biological Assay Models, Statistical Animal Testing Alternatives
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Coating independent cytotoxicity of citrate- and PEG-coated silver nanoparticles on a human hepatoma cell line.

Journal of environmental sciences (China) Jul 13, 2016
The antibacterial potential of silver nanoparticles (AgNPs) resulted in their increasing incorporation into consumer, industrial and biomedical products. Therefore, human and environmental exposure to AgNPs (either as an engineered product or a conta...
Metal Nanoparticles Citric Acid Humans Cell Line, Tumor Silver Anti-Bacterial Agents Hazardous Substances Liver Neoplasms Polyethylene Glycols Carcinoma, Hepatocellular
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Modeling the binding affinity of structurally diverse industrial chemicals to carbon using the artificial intelligence approaches.

Environmental science and pollution research international Jul 11, 2015
Binding affinity of chemical to carbon is an important characteristic as it finds vast industrial applications. Experimental determination of the adsorption capacity of diverse chemicals onto carbon is both time and resource intensive, and developmen...
Artificial Intelligence Models, Theoretical Algorithms Quantitative Structure-Activity Relationship Charcoal Hazardous Substances Industrial Waste Adsorption Carbon
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Machine Learning of Toxicological Big Data Enables Read-Across Structure Activity Relationships (RASAR) Outperforming Animal Test Reproducibility.

Toxicological sciences : an official journal of the Society of Toxicology Sep 1, 2018
Earlier we created a chemical hazard database via natural language processing of dossiers submitted to the European Chemical Agency with approximately 10 000 chemicals. We identified repeat OECD guideline tests to establish reproducibility of acute o...
Humans Machine Learning Big Data Models, Theoretical Structure-Activity Relationship Reproducibility of Results Sensitivity and Specificity Animals Animal Testing Alternatives Hazardous Substances Data Mining Databases, Chemical
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Part 1. Statistical Learning Methods for the Effects of Multiple Air Pollution Constituents.

Research report (Health Effects Institute) Jun 1, 2015
INTRODUCTION: The United States Environmental Protection Agency (U.S. EPA*) currently regulates individual air pollutants on a pollutant-by-pollutant basis, adjusted for other pollutants and potential confounders. However, the National Academies of S...
United States Environmental Protection Agency Computer Simulation Humans Aged Dogs Animals Air Pollutants Respiratory Tract Diseases Bayes Theorem Artificial Intelligence Particulate Matter Hazardous Substances Air Pollution Prospective Studies United States Environmental Exposure Environmental Monitoring Data Interpretation, Statistical
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