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020 _a9783031643736
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024 7 _a10.1007/978-3-031-64373-6
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
100 1 _aHughes, James.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_984946
245 1 0 _aAI Versus Epidemics
_h[electronic resource] /
_cby James Hughes, Sheridan Houghten, Michael Dubé, Daniel Ashlock, Joseph Alexander Brown, Wendy Ashlock, Matthew Stoodley.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2024.
300 _aXI, 97 p. 57 illus., 35 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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490 1 _aSynthesis Lectures on Learning, Networks, and Algorithms,
_x2690-4314
505 0 _aChapter 1 Introduction -- Chapter 2 Evolutionary Computation -- Chapter 3 Graph Compression -- Chapter 4 Network Induction.
520 _aThis book presents algorithms and tools that are designed to model and extract information from personal contact networks that 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. In addition, this book: Demonstrates applied techniques for researchers and professionals working on solving problems related to epidemics Explains why personal contact networks are the key to understanding the dynamics of an epidemic managing related issues Provides solutions to problems that occur when creating and utilizing models of large populations About the Authors: James Alexander Hughes, Ph.D., is a Professor in the Department of Computer Science at St. Francis Xavier University. Sheridan Houghten, Ph.D., is a Professor in the Department of Computer Science at Brock University. Michael Dubé is a Ph.D. student at the University of Guelph. He earned his Master’s degree from Brock University. Matthew Stoodley, Ph.D., is a Senior Bioinformatics Analyst at the University Health Network in Toronto. Daniel Ashlock, Ph.D., was the Chair of the Department of Mathematics and Statistics at the University of Guelph. Joseph Alexander Brown, Ph.D., is an Assistant Teaching Professor at Thompson Rivers University.
650 0 _aArtificial intelligence.
_958441
650 0 _aMachine learning.
_955059
650 0 _aMedical sciences.
_965984
650 0 _aPublic health.
_961312
650 0 _aApplication software.
650 0 _aAlgorithms.
_958677
650 1 4 _aArtificial Intelligence.
_958441
650 2 4 _aMachine Learning.
_955059
650 2 4 _aHealth Sciences.
_965987
650 2 4 _aPublic Health.
_961312
650 2 4 _aComputer and Information Systems Applications.
650 2 4 _aAlgorithms.
_958677
700 1 _aHoughten, Sheridan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_984947
700 1 _aDubé, Michael.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_984948
700 1 _aAshlock, Daniel.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_984949
700 1 _aBrown, Joseph Alexander.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_984950
700 1 _aAshlock, Wendy.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_984951
700 1 _aStoodley, Matthew.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_984952
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031643729
776 0 8 _iPrinted edition:
_z9783031643743
776 0 8 _iPrinted edition:
_z9783031643750
830 0 _aSynthesis Lectures on Learning, Networks, and Algorithms,
_x2690-4314
_984953
856 4 0 _uhttps://doi.org/10.1007/978-3-031-64373-6
912 _aZDB-2-SXSC
999 _c63681
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