Automated Elicitation of Human and Ecological Health Indicators: An LLM-Based Practical Implementation for One Digital Health.

This paper presents a new method for automating the identification of human and ecological health indicators using the One Digital Health framework, which combines One Health and Digital Health principles. By applying mainly Large Language Models, we conduct a systematic literature review on urban freshwater environments. This automation streamlines the process of finding and analyzing relevant research, allowing us to extract vital health indicators related to urban aquatic ecosystems and human wellness. The findings support the OneAquaHealth project's goals, enhancing environmental monitoring and linking human, animal, and environmental health in a digital context.

Duke Scholars

Author Arriel Benis Biomedical Engineering