AI in Public Health and Epidemiology: Advancing Population Well-Being

Abstract

Artificial Intelligence (AI) is increasingly applied in public health and epidemiology to predict disease outbreaks, optimize healthcare resources, and design effective interventions for population well-being. By processing massive datasets from electronic health records, mobility data, and social media, AI models enhance surveillance, accelerate response times, and support evidence-based policymaking. This article examines applications of AI in infectious disease modeling, chronic disease management, health policy, and global health security, while addressing challenges of data ethics and equity.

Keywords

Artificial Intelligence Public Health Epidemiology Disease Surveillance Health Policy

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