Mission and Objectives
Artificial intelligence is transforming public health, offering new ways to access information, generate insights, and support decision-making. This tutorial provides digital health professionals – including researchers, infection control experts, nurses, and doctors – with a practical introduction to generative AI and its applications in public health.
Participants will explore how AI can enhance information retrieval and decision support by leveraging domain-specific knowledge through custom AI assistants. The session covers fundamental concepts such as retrieval-augmented generation (RAG) and prompt engineering, along with practical risks like AI-generated misinformation.
A hands-on component will allow attendees to apply these concepts, working with curated public health documents to customise and deploy a retrieval-based AI system. This tutorial is designed for digital health professionals seeking to understand and apply AI tools in their daily work, ensuring AI-driven insights are relevant, reliable, and support human decision-making.
Intended Audience
This tutorial is designed for digital health professionals who want to understand and apply AI
in their work, including:
- Public health researchers
- Epidemiologists and infection control experts
- Healthcare policymakers
- Clinicians, nurses, and frontline healthcare professionals
- Health data analysts and informaticians
- AI and digital health innovators interested in practical applications
Participants should have a general understanding of digital health tools but don’t need prior
AI expertise.
Expected Outcomes
By the end of the tutorial, participants will:
- Understand the fundamentals of generative AI, retrieval-augmented generation (RAG), and prompt engineering
- Identify the strengths, limitations, and risks of AI-driven decision support
- Gain hands-on experience customising and deploying an AI assistant using public health data
- Develop practical strategies for integrating AI tools into research, policy, and clinical decision-making
- Recognise the importance of human oversight in AI-driven insights
- Leave with a framework for safely and effectively using AI in their professional practice
Format and Schedule
| Time | Session | Description |
|---|---|---|
| 00:00 00:40 | Lecture: AI in Public Health | Introduction to generative AI, retrieval-augmented generation (RAG), and prompt engineering. Discussion of strengths, limitations, and misinformation risks. |
| 00:40 01:20 | Hands-on Workshop | Participants work with curated public health documents to customise and deploy a retrieval-based AI system. Guided exercises help tailor AI models for professional use cases. |
| 01:20 01:30 | Q&A and Wrap-Up | Final discussion on best practices, implementation challenges, and future AI applications in public health. |
Speakers
Hudson&Hayes