About the site
Weekly essays and working papers from Min Wu, author of Artificial Intelligence in Public Health (Springer Nature, 2026).
Our story · Content map · The book and author
Our story
This site isn't a general AI blog. It's the living companion to Artificial Intelligence in Public Health — the place where the ideas in the book keep developing between editions. Every essay, preprint, and prototype published here exists to serve one goal: extending and improving the book's ideas. Nothing gets written just because it's trending. If it doesn't sharpen, test, or extend a specific chapter, it doesn't belong here — though the strongest of it may well end up shaping a future edition.
Content map
Each chapter below links to the published theory in the textbook, plus whatever's currently active — concept maps, SSRN preprints, and code. Chapters without active entries are open ground.
Chapter 1 — Introduction
Read the chapter →
No active preprints, concept maps, or repos yet.
Chapter 2 — AI Components
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No active preprints, concept maps, or repos yet.
Chapter 3 — Design Models for AI in Public Health
Read the chapter →
No active preprints, concept maps, or repos yet.
Chapter 4 — Evaluation Models for AI in Public Health
Concept map — ICV-4-1: An interactive, clickable map of the core concepts behind evaluating AI systems — where validity, reliability, and equity meet in practice. Built as a teaching companion to the chapter. Open the map →
Chapter 5 — Data Issues for AI
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No active preprints, concept maps, or repos yet.
Chapter 6 — Public Health Domain Data for AI
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No active preprints, concept maps, or repos yet.
Chapter 7 — AI Applications for Public Health Systemic Factors
Framework — EquiRisk: Operationalizing equity-aware risk stratification for diabetes management in food-desert geographies. Companion SSRN preprint to the chapter.
Wu, Min. EquiRisk: Operationalizing Equity-Aware Risk Stratification for Diabetes Management in Food Deserts. Jan 28, 2026. doi:10.2139/ssrn.6150926 Read on SSRN →
Code — EquiRisk · Food Deserts Repo: A working implementation of the EquiRisk framework with synthetic data. View on GitHub →
Chapter 8 — AI Applications for Public Health Personal Responsibilities
Framework — PAPO: A Policy-Aware Personalized Opportunity framework integrating individual risk, local policy levers, and intervention feasibility for heatwave public health interventions.
Wu, Min. PAPO: A Policy-Aware Personalized Opportunity Framework for Heatwave Public Health Interventions. Feb 8, 2026. doi:10.2139/ssrn.6198260 Read on SSRN →
Code — PAPO · Heatwave AI Repo: A simulation of the PAPO framework applied to extreme-heat public health interventions. View on GitHub →
Framework — PMCO-AI: Personalized Motivation, Capability, and Opportunity in the AI era, illustrated through a dementia-care case.
Wu, Min. PMCO-AI: Personalized Motivation, Capability, and Opportunity in the AI Era — A Case Illustration in Dementia Care. July 16, 2026. Read on SSRN →
Chapter 9 — From Acceptance to Thinking Partner
Read the chapter →
No active preprints, concept maps, or repos yet.
Chapter 10 — AI and Workforce for Public Health
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No active preprints, concept maps, or repos yet.
Chapter 11 — Challenges and Opportunities in the Future
Read the chapter →
No active preprints, concept maps, or repos yet.
Pending chapter assignment
Framework — C-E-A: Compliance, Efficacy, and Autonomy — a framework for AI agents, illustrated through a personalized robotic-care case. A new framework, not yet mapped to a specific chapter.
Wu, Min. The C-E-A Framework for AI Agents: Compliance, Efficacy, and Autonomy — A Case Illustration in Personalized Robotic Care. July 30, 2026. Read on SSRN →
The book and author
The book. Artificial Intelligence in Public Health (Springer Nature, 2026), by Min Wu, is the foundation this entire site is built to extend. The essays, frameworks, and code above are candidates being tested here.
As a member of the Springer Nature Author Affiliate Program, I may earn a small commission from purchases made through this link: tidd.ly/4mH9389
About Min Wu. Min Wu earned his Ph.D. in medical informatics from the University of North Carolina at Chapel Hill in 2003. He is now an associate professor in the Zilber College of Public Health at the University of Wisconsin, Milwaukee, where his research focuses on identifying unmet public health needs and implementing technological solutions. His writing has appeared in the Journal of Medical Informatics, the Journal of Medical Systems, and Academic Radiology, and he is a past recipient of the Best Article Award from the Journal of Digital Imaging. He has taught health informatics graduate courses for more than 20 years, giving him a deep, broad grounding in biomedical informatics. His recent review articles cover big-data applications in biomedical research and health care, and wearable technology in health care, and he closely tracks AI's impact on public health — from preventing disease to promoting health and prolonging life.
Browse all repositories on GitHub: github.com/Min-PH