Rise of the Machines - Artificial Intelligence in Healthcare Epidemiology

Abstract

Purpose of Review: This article delves into the current applications, challenges, and future directions of artificial intelligence (AI) in healthcare epidemiology, focusing on its integration into infection surveillance, prediction modelling, antimicrobial resistance, and antimicrobial stewardship. Recent Findings: AI has the potential to transform key areas in healthcare epidemiology. AI-driven systems improve infection surveillance by automating data collection and analysis, enabling real-time monitoring and rapid identification of infection trends and outbreaks. Predictive modeling benefits from AI through processing of big data and other unconventional data sources. AI can augment antimicrobial stewardship by individualizing antimicrobial therapy, reducing inappropriate use. Finally, AI aids in addressing antimicrobial resistance by facilitating rapid detection of resistance patterns, enhancing surveillance, and accelerating the discovery of new antibiotics. Together, these advancements promise more effective management of infectious diseases and optimized healthcare interventions. Summary: The role of AI in healthcare epidemiology is still getting defined but is showing a lot of potential in many areas. Ongoing challenges include data quality, ethical considerations, and the need for explainable AI models to ensure transparency and trust among healthcare professionals.