The future of environmental health modeling: leveraging artificial intelligence to combat air pollution challenges
Year: 2025
Type: article
Abstract: Recent advancements in artificial intelligence (AI), particularly large-scale multimodal models, are transforming various sectors by surpassing human performance in a wide range of tasks. Although AI is increasingly applied to tackle environmental issues such as air pollution, its use in analyzing the relationship between pollution and human health remains limited. Given AI’s growing capabilities in real-time human-environment monitoring, multimodal data integration, predictive health modeling, and intelligent data processing, this perspective explores AI’s potential in advancing research on the health effects of air pollution. We emphasize the role of AI in enabling personalized risk assessments, supporting informed decision making, and uncovering previously hidden mechanisms linking the environment to health. By synthesizing current research, this article highlights how AI can accelerate scientific discovery and inform targeted public health interventions and policies, offering a paradigm shift in addressing this pressing global challenge.
Authors: Bin Zhang, Jian Sun
Institutions: Kanagawa University, Xi'an Jiaotong University
Language: English
Subfield: Health, Toxicology and Mutagenesis
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4411218954