POPULATION HEALTH BREAKTHROUGHS: HARNESSING AI FOR PREDICTIVE PUBLIC HEALTH OUTCOMES

Abstract

Globally, population health management techniques are being revolutionized by the intersection of public health and artificial intelligence. This article explores the use of AI and machine learning technology to predict health outcomes, allowing for proactive approaches to resource allocation, epidemic response, and chronic disease management. It illustrates how AI systems have greatly enhanced the identification of at-risk groups and the prediction of disease outbreaks through extensive case studies spanning a variety of demographics. Public health organizations can now carry out focused, evidence-based interventions that improve population health outcomes by combining social determinants of health with conventional clinical data. The article highlights urban and rural uses of AI-driven healthcare while addressing implementation obstacles, ethical issues, and future possibilities.