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<p>The rapid advancement of artificial intelligence (AI) presents unprecedented opportunities and challenges for assessing planetary health, particularly in environmental health. As a key determinant of human well-being, the environment significantly influences health. Although the application of AI in these areas has garnered increasing attention, a comprehensive evaluation framework is still lacking. In this review, we bridge this gap by proposing a unified evaluation framework that spans the entire environmental health research continuum, from modeling environmental exposures to assessing health outcomes and inferring causal relationships. We synthesize recent methodological innovations, application scenarios, and emerging trends across these interconnected domains. Our work highlights how AI can enhance accuracy, scalability, and causal understanding in environmental health studies. By emphasizing this integrated perspective, this review underscores AI’s synergistic potential in addressing complex environmental health challenges and informing planetary health strategies.</p>

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Artificial Intelligence in Environment and Human Health: Progress, Opportunities and Challenges

  • 期刊论文

  • 发表日期：

    2025年11月17日

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  • Dongyang Han,
  • Yanyi Xu,
  • Luofei Lin,
  • Xia Meng,
  • Renjie Chen,
  • Haidong Kan

摘要

The rapid advancement of artificial intelligence (AI) presents unprecedented opportunities and challenges for assessing planetary health, particularly in environmental health. As a key determinant of human well-being, the environment significantly influences health. Although the application of AI in these areas has garnered increasing attention, a comprehensive evaluation framework is still lacking. In this review, we bridge this gap by proposing a unified evaluation framework that spans the entire environmental health research continuum, from modeling environmental exposures to assessing health outcomes and inferring causal relationships. We synthesize recent methodological innovations, application scenarios, and emerging trends across these interconnected domains. Our work highlights how AI can enhance accuracy, scalability, and causal understanding in environmental health studies. By emphasizing this integrated perspective, this review underscores AI’s synergistic potential in addressing complex environmental health challenges and informing planetary health strategies.