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| Autore: |
Hughes Gareth
|
| Titolo: |
Applications of Information Theory to Epidemiology
|
| Pubblicazione: | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica: | 1 online resource (238 p.) |
| Soggetto topico: | Biology, life sciences |
| Research & information: general | |
| Soggetto non controllato: | Asiatic citrus canker |
| Atangana-Baleanu derivative | |
| average mutual information | |
| balance | |
| Bayes' rule | |
| binormal | |
| Caputo derivative | |
| Caputo-Fabrizio derivative | |
| deployment | |
| deterministic dynamics | |
| diagnostic information | |
| diagnostic test | |
| direct assay | |
| early detection | |
| Ebola model | |
| empirical | |
| entropy | |
| epidemic model | |
| evaluation | |
| expected mutual information | |
| field diagnostic | |
| Fisher scoring algorithm | |
| forecast | |
| HIV/AIDS epidemic | |
| information theory | |
| Jensen-Shannon divergence | |
| latent class | |
| leaf plot | |
| likelihood ratio | |
| multiple diagnostic tests | |
| mutual information | |
| n/a | |
| negative predictive value | |
| Newton-Raphson procedure | |
| numerical results | |
| observational study | |
| positive predictive value | |
| predictive ROC curve | |
| prevalence | |
| probability | |
| PROC curve | |
| PV-ROC curve | |
| regression model | |
| relative entropy | |
| ROC curve | |
| scent signature | |
| selection bias | |
| sensitivity | |
| Shannon entropy | |
| specificity | |
| SS-ROC curve | |
| SS/PV-ROC plot | |
| stochastic processes | |
| time series | |
| transient behavior | |
| urinary bladder cancer | |
| vaccination and treatment intervention controls | |
| Persona (resp. second.): | HughesGareth |
| Sommario/riassunto: | • 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. |
| Titolo autorizzato: | Applications of Information Theory to Epidemiology ![]() |
| Formato: | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910557759303321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |