Research and Application of Artificial Intelligence and Big Data in Infectious Disease Prevention and Control
Xiaoqing Tang, Xiupeng Yan, Junbiao Chang, Minghui Zhao · 2024
With the continuous spread and globalization of infectious diseases, infectious disease prevention and control has become an important task for both countries and the world. Traditional infectious disease monitoring methods often rely on manual collection and analysis of data, which is inefficient and easily limited by human errors. However, the development of artificial intelligence and big data technology has provided new opportunities for infectious disease prevention and control. This article introduces the application of artificial intelligence in infectious disease monitoring. By using artificial intelligence algorithms and models, real-time monitoring and analysis of infectious disease data can be carried out, predicting the spread trend and risk of infectious diseases. This helps to detect and report infectious disease outbreaks, thus taking corresponding prevention and control measures and reducing the spread and impact of the epidemic. At the same time, this article explores the application of big data in infectious disease prevention and control. By using big data technology, in-depth mining and analysis of patient case data, virus gene sequences, transmission chain information, and other data can be carried out to discover the characteristics and patterns of infectious diseases, and be used to build an infectious disease warning system to predict and prevent the occurrence of infectious diseases in advance. Finally, this article discusses the application cases of artificial intelligence and big data in infectious disease prevention and control. By combining artificial intelligence and big data technology, the entire process of monitoring and management of infectious diseases can be achieved.