| Sumario: | The convergence of artificial intelligence (AI), biotechnology, and biomedical big data holds promise to transform understanding of human health and disease. Driven by the increasing availability and ability to generate, collect, and analyze environmental and biomedical data along with advanced computing power, AI and machine learning (ML) applications are rapidly developing in research and health. To explore opportunities for leveraging emerging developments in AI and ML to advance multimodal data integration, the National Academies of Sciences, Engineering, and Medicine hosted a workshop titled Advances in Multimodal Artificial Intelligence to Enhance Environmental and Biomedical Data Integration on June 14-15, 2023. The workshop focused on recent developments in AI and other data-driven approaches to integrate biomedical and environmental health data; the exploration of promising applications in human health and disease; and the ethical, social, and policy implications and challenges of health data collection and integration. This publication summarizes the presentations and discussions of the workshop.
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