Adverse outcome pathway-informed machine learning for predicting vascular toxicity of emerging organic pollutants.
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| Title: | Adverse outcome pathway-informed machine learning for predicting vascular toxicity of emerging organic pollutants. |
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| Authors: | Siewetcheu Toukak A; School of Environmental Science and Engineering, Tianjin Key Lab of Biomass/Wastes Utilization, Tianjin University, Tianjin 300350, China. liningec@tju.edu.cn., Gao W; School of Environmental Science and Engineering, Tianjin Key Lab of Biomass/Wastes Utilization, Tianjin University, Tianjin 300350, China. liningec@tju.edu.cn., Wan S; School of Environmental Science and Engineering, Tianjin Key Lab of Biomass/Wastes Utilization, Tianjin University, Tianjin 300350, China. liningec@tju.edu.cn., Li N; School of Environmental Science and Engineering, Tianjin Key Lab of Biomass/Wastes Utilization, Tianjin University, Tianjin 300350, China. liningec@tju.edu.cn., Chen G; School of Environmental Science and Engineering, Tianjin Key Lab of Biomass/Wastes Utilization, Tianjin University, Tianjin 300350, China. liningec@tju.edu.cn.; School of Mechanical Engineering, Tianjin University of Commerce, Tianjin 300134, China.; School of Ecology and Environment, Xizang University, Lhasa 850000, China. |
| Source: | Environmental science. Processes & impacts [Environ Sci Process Impacts] 2026 May 01; Vol. 28 (4), pp. 1064-1080. Date of Electronic Publication: 2026 May 01. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Royal Society of Chemistry Country of Publication: England NLM ID: 101601576 Publication Model: Electronic Cited Medium: Internet ISSN: 2050-7895 (Electronic) Linking ISSN: 20507887 NLM ISO Abbreviation: Environ Sci Process Impacts Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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