AI for science: Predicting infectious diseases
University of Chinese Academy of Sciences · Institute of Automation · +5 more institutions
Abstract
The global health landscape has been persistently challenged by the emergence and re-emergence of infectious diseases. Traditional epidemiological models, rooted in the early 20th century, have provided foundational insights into disease dynamics. However, the intricate web of modern global interactions and the exponential growth of available data demand more advanced predictive tools. This is where AI for Science (AI4S) comes into play, offering a transformative approach by integrating artificial intelligence (AI) into infectious disease prediction. This paper elucidates the pivotal role of AI4S in enhancing and, in some instances, superseding traditional epidemiological methodologies. By harnessing AI's…
Citation impact
- FWCI
- 52.67
- Percentile
- 100%
- References
- 227
Authors
8- APAlexis Pengfei Zhao
University of Chinese Academy of Sciences, Institute of Automation
- SLShuangqi Li
Cornell University
- ZCZhidong CaoCorresponding
University of Chinese Academy of Sciences, Institute of Automation
- PJPaul Jen‐Hwa Hu
University of Utah
- JWJiaojiao Wang
Institute of Automation, University of Chinese Academy of Sciences
Topics & keywords
- Infectious disease (medical specialty)
- Transformative learning
- Data science
- Computer science
- Adaptability
- Disease
- Citizen science
- Artificial intelligence