AI Versus Epidemics (2024) (Synthesis Lectures on Learning, Networks, and Algorithms)

By: James Hughes and Sheridan Houghten and Michael Dubé and Daniel Ashlock and Joseph Alexander Brown and Wendy Ashlock and Matthew Stoodley

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Synopsis: 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.

Book Quality:: Publisher Quality
ISBN-13:: 9783031643736
Related ISBNs:: 9783031643729
Publisher:: Springer International Publishing
Date of Addition:: 10/26/24
Copyrighted By:: The Editor
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Computers and Internet, Mathematics and Statistics, Medicine
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.