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Building the Foundations of AI-Driven Toxicology: How to Use Fragmented Data for Mechanism-Based Human Health Risk Assessment

Year: 2026

Type: article

Source: Environmental Science & Technology

DOI: 10.1021/acs.est.5c17092

Authors: Bin Wang, Tianxiang Wu, Yingqing Shou, Yu Ma, Mengyuan Ren, Pablo Gago-Ferrero, Daniel Schlenk, Mingliang Fang

Institutions: Peking University, National Health and Family Planning Commission, Fudan University, Consejo Superior de Investigaciones Científicas, Institute of Environmental Assessment and Water Research

Language: English

Topic: Environmental Toxicology and Ecotoxicology

Subfield: Health, Toxicology and Mutagenesis

Field: Environmental Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

Funder: National Natural Science Foundation of China

Award: G3927579139

OpenAlex ID: W7170078323

FWCI:

Cites: 62

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