ARTIFICIAL INTELLIGENCE AND DEEP LEARNING INPUBLIC HEALTH SURVEILLANCE: A REVIEW WITH EMPHASISON SAUDI ARABIA

Background: Effective surveillance and timely detection of infectious diseases are crucial for protecting population health. Artificial intelligence (AI) and deep learning models have emerged as powerful tools to improve disease monitoring, forecasting and decision making. Saudi Arabia, with ambitious Vision 2030 health reforms, provides a unique case study for applying these technologies.

Methods: A narrative review of peer reviewed articles from 2010,2025 was conducted using databases such as PubMed and Google Scholar. Emphasis was placed on AI and deep learning approaches for disease surveillance, outbreak prediction and public health decision support, with a focus on models evaluated in Saudi Arabia or Gulf Cooperation Council countries. Key findings were extracted and synthesised. We also outline a methodological approach for developing a deep learning model to forecast influenza like illness in Saudi Arabia using publicly available surveillance data and exogenous variables.