The Potential Role of Artificial Intelligence in Public Health — A Scoping Review

Abstract

Artificial intelligence (AI) is a broad field encompassing various techniques, including machine learning, natural language processing, and computer vision. AI, which refers to algorithms integrated into systems and tools, learns from data to be able to perform automated tasks without explicit human programming. AI is particularly useful for tasks requiring pattern recognition, prediction, and data analysis. In healthcare, for instance, AI applications have been used to enhance image analysis, streamline operations, enable personalized and predictive healthcare, and
support clinical decision-making. In public health, AI has been used for spatial modelling, risk prediction, misinformation control, public health surveillance, disease forecasting, and epidemic and pandemic modelling. Additionally, conversational AI interventions have been used to support smoking cessation and reducing alcohol intake, and AI-assisted apps have been used to improve exercise technique. Other uses of AI in public health remain hypothesised but un- or under-explored in practice, for
instance in public communication. The COVID-19 pandemic, in particular, highlighted both the challenges and opportunities for using AI in public health. The scale and severity of the pandemic underscored the need for more efficient and effective interventions, and AI was used for disease
surveillance, contact tracing, combating misinformation, predicting transmission patterns, and forecasting disease spread. This review will explore the potential role of AI in public health, including potential benefits and challenges.