Abstract
Artificial Intelligence (AI) has emerged as a transformative tool in managing epidemics, offering innovative solutions to detect, predict, and mitigate the spread of infectious diseases. This paper explores the role of AI in tackling recent outbreaks, such as COVID-19, Ebola, and Zika, emphasizing its contributions to real-time data analysis, contact tracing, and outbreak prediction. Key AI applications, including machine learning models for disease forecasting, natural language processing for analyzing public health data, and AI-powered diagnostic tools, are examined. Additionally, the study discusses the challenges of implementing AI in epidemic management, such as data privacy concerns, technological infrastructure disparities, and the need for global collaboration. Lessons from these outbreaks underline the importance of integrating AI into global health systems to enhance preparedness, response, and resilience against future public health crises.
Published Version
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