Artificial intelligence, modelling communicable diseases: one of the applications in Epidemiology

Background and Aims: Artificial intelligence is becoming a very relevant tool in contemporary science. The world is also facing the phenomena of emerging and re-emerging infectious diseases. The aim of this study is to systematically review research that has addressed the use of artificial intelligence in infectious disease modeling. Methods: A search for reputable scientific articles and sources from PubMed, Google Scholar, and Web of Science databases was conducted and various applications of this technology were analyzed. The final database search was conducted on October ۳۱, ۲۰۲۵. The identified publications were reviewed based on the specified inclusion and exclusion criteria to determine eligibility. The risk of bias was assessed, and the findings were synthesized narratively and quantitatively. Results: In total, this review identified ۳۵ studies that addressed disease modeling using artificial intelligence. Machine learning and deep learning modeling have been increasingly used to predict disease outbreaks. In comparing the accuracy results of AI models with classical epidemiological approaches, AI models have been highly validated. However, there were significant considerations and limitations related to data quality and ethical considerations. Conclusion: The use of AI in the infectious disease surveillance system can play a significant role and can bring about a tremendous transformation in the scientific and easier application of these models for health policymakers. However, the need for further research and further redefinition of models in this field is felt.

کلیدواژه ها:

Artificial Intelligence ، Modelling Communicable Diseases ، Epidemiology