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| Full Title | AI Versus Epidemics |
|---|---|
| Author(s) | James Hughes, Sheridan Houghten, Michael Dubé, Daniel Ashlock, Joseph Alexander Brown, Wendy Ashloc |
| Edition | |
| ISBN | 9783031643736, 9783031643729 |
| Publisher | Springer |
| Format | PDF and EPUB |
This book presents algorithms and tools that are designed to model and extract information from personal contact networks, which represent which individuals in a population are physically in contact with one another. The authors developed these tools based on research they conducted during the COVID-19 pandemic, with the goal of improving responses to epidemics in the future. The book provides methods for modelling the transmission of infection across a population. The authors explain how an epidemic model can be used to strategically distribute vaccines and minimize the spread of a virus. The book shows how evolutionary computation, graph compression, and network induction can be utilized to manage issues that arise from an epidemic.
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