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

Area of Science:

• Environmental health sciences
• Planetary health
• Artificial intelligence applications

Background:

• The environment is a critical factor influencing human well-being and planetary health.
• Artificial intelligence (AI) is increasingly applied in environmental health research, but lacks a unified evaluation framework.
• Assessing environmental health impacts is crucial for understanding planetary health challenges.

Purpose of the Study:

• To propose a unified evaluation framework for artificial intelligence in environmental health research.
• To bridge the gap in current AI evaluation methodologies for environmental health.
• To synthesize innovations, applications, and trends in AI for environmental health.

Main Methods:

• Comprehensive literature review of AI applications in environmental health.
• Synthesis of methodological innovations across the environmental health research continuum.
• Analysis of AI's role in exposure modeling, health outcome assessment, and causal inference.

Main Results:

• AI enhances accuracy, scalability, and causal understanding in environmental health studies.
• The proposed framework integrates AI applications from exposure assessment to health outcomes.
• Identified emerging trends and innovative AI methodologies in the field.

Conclusions:

• A unified AI evaluation framework is essential for advancing environmental health and planetary health strategies.
• AI holds significant synergistic potential for addressing complex environmental health issues.
• This framework supports informed decision-making for planetary health initiatives.