How explainable AI and One Health principles can be integrated to combat zoonotic diseases and cross-sector health threats.
Case study: geospatial AI applied to public health in Essex County for disease mapping, resource allocation, and health equity.
Analysis of how AI could transform public health planning—including forecasting and resource allocation—while raising equity concerns.
Research on using generative AI to correct vaccine misinformation through targeted, personalized message interventions.
Research on harnessing AI/ML to enhance public health surveillance: pathogen detection, outbreak forecasting, and data integration.
Review of AI applications in disease surveillance: real-time monitoring, predictive analytics, and early outbreak detection systems.
Overview of geospatial AI and its applications in GIS for public health mapping, environmental analysis, and decision support.
Government agency generative AI policy covering acceptable use, data handling, privacy protections, and human oversight requirements.
Perspective on applying machine learning in healthcare: cautions against shortcuts, emphasizes evidence, validation, and equity.
Framework for transforming public health practice with AI, covering core capabilities, governance, and equity-centered implementation.
Review of next-generation geospatial AI methods and applications in public health, environmental monitoring, and urban planning.
Analysis of the growing environmental impact of AI data centers' rising energy demands on climate and sustainability goals.
This webinar on using AI in health departments for chronic disease prevention, featuring real examples, ethical guidance, and tips to get started.
Explainer on why large language models hallucinate: mechanisms, causes, and implications for health information reliability.
Guidance on potential use of AI in disaster risk and emergency management for prediction, response coordination, and recovery.
Study on AI-powered living health promotion campaigns tailored to U.S. communities using real-time data and personalization.
Framework for integrating health equity considerations into AI design and deployment for public health applications.
Policy on acceptable and responsible use of AI tools by employees: principles, prohibited uses, and oversight requirements.
How modernized surveillance systems leveraging AI and data sharing can improve global public health security preparedness.
Report on the AI capability gap between advanced AI developers and public health agencies, and strategies to close the divide.