THE USE OF ARTIFICIAL INTELLIGENCE IN EPIDEMIC MANAGEMENT
Abstract
This article analyzes the application of artificial intelligence technologies for the early detection and effective management of epidemics. A predictive model based on pharmacy sales data, outpatient clinic visits, online search trends, and climate factors is proposed. The “Triple Confirmation” algorithm is introduced as a method for cross-validating multiple independent data sources to generate an early warning system. The study highlights the advantages, practical relevance, economic efficiency, and the technological and legal challenges of implementing this approach. Artificial intelligence–based epidemiological monitoring is presented as a key tool for transitioning healthcare systems toward a proactive management model.
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