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Book
Applications of Information Theory to Epidemiology
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Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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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.

Keywords

Research & information: general --- Biology, life sciences --- Ebola model --- Caputo derivative --- Caputo-Fabrizio derivative --- Atangana-Baleanu derivative --- numerical results --- entropy --- information theory --- multiple diagnostic tests --- mutual information --- relative entropy --- balance --- Jensen-Shannon divergence --- observational study --- selection bias --- probability --- forecast --- likelihood ratio --- positive predictive value --- negative predictive value --- diagnostic information --- Shannon entropy --- epidemic model --- transient behavior --- vaccination and treatment intervention controls --- diagnostic test --- evaluation --- ROC curve --- PROC curve --- binormal --- prevalence --- Bayes' rule --- leaf plot --- expected mutual information --- predictive ROC curve --- PV-ROC curve --- SS-ROC curve --- SS/PV-ROC plot --- empirical --- urinary bladder cancer --- sensitivity --- specificity --- HIV/AIDS epidemic --- regression model --- Newton-Raphson procedure --- Fisher scoring algorithm --- time series --- early detection --- Asiatic citrus canker --- latent class --- field diagnostic --- scent signature --- direct assay --- deployment --- average mutual information --- stochastic processes --- deterministic dynamics --- Ebola model --- Caputo derivative --- Caputo-Fabrizio derivative --- Atangana-Baleanu derivative --- numerical results --- entropy --- information theory --- multiple diagnostic tests --- mutual information --- relative entropy --- balance --- Jensen-Shannon divergence --- observational study --- selection bias --- probability --- forecast --- likelihood ratio --- positive predictive value --- negative predictive value --- diagnostic information --- Shannon entropy --- epidemic model --- transient behavior --- vaccination and treatment intervention controls --- diagnostic test --- evaluation --- ROC curve --- PROC curve --- binormal --- prevalence --- Bayes' rule --- leaf plot --- expected mutual information --- predictive ROC curve --- PV-ROC curve --- SS-ROC curve --- SS/PV-ROC plot --- empirical --- urinary bladder cancer --- sensitivity --- specificity --- HIV/AIDS epidemic --- regression model --- Newton-Raphson procedure --- Fisher scoring algorithm --- time series --- early detection --- Asiatic citrus canker --- latent class --- field diagnostic --- scent signature --- direct assay --- deployment --- average mutual information --- stochastic processes --- deterministic dynamics


Book
Applications of Information Theory to Epidemiology
Author:
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

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.

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