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Adverse outcome pathway-informed machine learning for predicting vascular toxicity of emerging organic pollutants.

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Bibliographic Details
Title: Adverse outcome pathway-informed machine learning for predicting vascular toxicity of emerging organic pollutants.
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
Description
ISSN:2050-7895
DOI:10.1039/d5em00562k