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dc.contributor.editorHughes, Gareth
dc.date.accessioned2021-05-01T15:14:55Z
dc.date.available2021-05-01T15:14:55Z
dc.date.issued2021
dc.identifierONIX_20210501_9783036503165_315
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/68569
dc.description.abstract• Applications of Information Theory to Epidemiology collects recent research findings on the analysis of diagnostic information and epidemic dynamics. • The collection includes an outstanding new review article by William Benish, providing both a historical overview and new insights. • In research articles, disease diagnosis and disease dynamics are viewed from both clinical medicine and plant pathology perspectives. Both theory and applications are discussed. • New theory is presented, particularly in the area of diagnostic decision-making taking account of predictive values, via developments of the predictive receiver operating characteristic curve. • New applications of information theory to the analysis of observational studies of disease dynamics in both human and plant populations are presented.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: generalen_US
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PS Biology, life sciencesen_US
dc.subject.otherEbola model
dc.subject.otherCaputo derivative
dc.subject.otherCaputo–Fabrizio derivative
dc.subject.otherAtangana–Baleanu derivative
dc.subject.othernumerical results
dc.subject.otherentropy
dc.subject.otherinformation theory
dc.subject.othermultiple diagnostic tests
dc.subject.othermutual information
dc.subject.otherrelative entropy
dc.subject.otherbalance
dc.subject.otherJensen–Shannon divergence
dc.subject.otherobservational study
dc.subject.otherselection bias
dc.subject.otherprobability
dc.subject.otherforecast
dc.subject.otherlikelihood ratio
dc.subject.otherpositive predictive value
dc.subject.othernegative predictive value
dc.subject.otherdiagnostic information
dc.subject.otherShannon entropy
dc.subject.otherepidemic model
dc.subject.othertransient behavior
dc.subject.othervaccination and treatment intervention controls
dc.subject.otherdiagnostic test
dc.subject.otherevaluation
dc.subject.otherROC curve
dc.subject.otherPROC curve
dc.subject.otherbinormal
dc.subject.otherprevalence
dc.subject.otherBayes’ rule
dc.subject.otherleaf plot
dc.subject.otherexpected mutual information
dc.subject.otherpredictive ROC curve
dc.subject.otherPV-ROC curve
dc.subject.otherSS-ROC curve
dc.subject.otherSS/PV-ROC plot
dc.subject.otherempirical
dc.subject.otherurinary bladder cancer
dc.subject.othersensitivity
dc.subject.otherspecificity
dc.subject.otherHIV/AIDS epidemic
dc.subject.otherregression model
dc.subject.otherNewton–Raphson procedure
dc.subject.otherFisher scoring algorithm
dc.subject.othertime series
dc.subject.otherearly detection
dc.subject.otherAsiatic citrus canker
dc.subject.otherlatent class
dc.subject.otherfield diagnostic
dc.subject.otherscent signature
dc.subject.otherdirect assay
dc.subject.otherdeployment
dc.subject.otheraverage mutual information
dc.subject.otherstochastic processes
dc.subject.otherdeterministic dynamics
dc.subject.othern/a
dc.titleApplications of Information Theory to Epidemiology
dc.typebook
oapen.identifier.doi10.3390/books978-3-0365-0317-2
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0
oapen.relation.isbn9783036503165
oapen.relation.isbn9783036503172
oapen.pages238
oapen.place.publicationBasel, Switzerland


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