The Role of AI in Predicting Epidemic Outbreaks

Authors

  • Pat Gonzalez
  • Chris Edwards
  • Sam Brown

Keywords:

artificial intelligence, epidemic, prediction, machine learning, data analysis

Abstract

This study examines the application of artificial intelligence in predicting epidemic outbreaks. By analyzing data patterns from previous outbreaks and using machine learning algorithms, the research assesses AI's ability to forecast potential health crises. The findings suggest that AI can significantly enhance early detection and response strategies, potentially minimizing the impact of future epidemics. Challenges and limitations of current AI methodologies are also discussed.

Author Biographies

Pat Gonzalez

PhD
University of Tokyo
7 Chome-3-1 Hongo, Bunkyo City, Tokyo 113-8654, Japan

Chris Edwards

PhD
Stanford University
450 Serra Mall, Stanford, CA 94305, United States

Sam Brown

MD
Bogomolets National Medical University
Peremohy Ave, 34, Kyiv, Ukraine, 01135

References

Svetlana, S., Liliya, K., & Vesela, K. (2025). Diffuse B cell large ileal lymphoma presenting with obstruction and associated with Hashimoto’s thyroiditis. Journal of Surgical Case Reports, 2025(4).

Published

2025-10-22

Issue

Section

Articles