A doctoral dissertation titled "Using Geospatial Analysis and Explainable Machine Learning to Examine Risk Factors of Out-of-Hospital Cardiac Arrest Survival Outcome" has been honored with the 2026 William L. Garrison Award for Best Dissertation in Computational Geography by the American Association of Geographers. The research developed Explainable GeoAI and Causal GeoAI methods, integrating geographic data with artificial intelligence to identify and address health disparities. These models aim to predict risks and pinpoint areas for intervention, with applications extending beyond cardiovascular disease to public health, medicine, urban planning, and environmental research. AI
IMPACT Develops novel GeoAI methods applicable to public health and urban planning, potentially improving intervention strategies for health disparities.
RANK_REASON The cluster describes an academic award for a dissertation focused on research using AI and geospatial analysis. [lever_c_demoted from research: ic=1 ai=1.0]
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- American Association of Geographers
- Explainable Machine Learning for Science and Medicine
- Harvard University
- Jielu Zhang
- Mastodon
- OpenScholar
- out-of-hospital cardiac arrest
- University of Guelph
- William L. Garrison Award for Best Dissertation in Computational Geography
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