Cancer mortality and morbidity patterns in the U.S. population : An interdisciplinary approach
This book is the first of its kind to describe interdisciplinary approaches to biomedical studies. It views analyses of biomedical data sets, such as cancer morbidity and mortality, from a different and richer than classic epidemiological perspective by using mathematical modeling methods, including...
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| Главные авторы: | , , |
|---|---|
| Формат: | Livre numérique |
| Язык: | Anglais |
| Опубликовано: |
New York, NY :
Springer New York
2009.
Cham : Springer Nature |
| Серии: | Statistics for Biology and Health
|
| Предметы: | |
| Online-ссылка: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Примечание: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Cancer Mortality and Morbidity Patterns in the U.S. Population, Texte imprimé, 9780387569857 • Cancer Mortality and Morbidity Patterns in the U.S. Population, Texte imprimé, 9781441926807 • Cancer mortality and morbidity patterns in the U.S. population, an interdisciplinary approach, K.G. Manton, Igor Akushevich, Julia Kravchenko, 2009, New York, Springer, 1 vol. (XV-455 p.), Statistics for biology and health, 978-0-387-78192-1 |
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| 100 | 1 | |a Manton, K.G. | |
| 245 | 1 | 0 | |a Cancer mortality and morbidity patterns in the U.S. population : |b An interdisciplinary approach |c by K.G. Manton, Igor Akushevich, Julia Kravchenko. |
| 260 | |a New York, NY : |b Springer New York. | ||
| 260 | |a Cham : |b Springer Nature, |c 2009. | ||
| 490 | 0 | |a Statistics for Biology and Health |x 2197-5671 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 0 | |a Cancer Contra Human: Cohabitation with Casualties? -- Cancer Modeling: How Far Can We Go? -- Cancer Risk Factors -- Standard and Innovative Statistical Methods for Empirically Analyzing Cancer Morbidity and Mortality -- Stochastic Methods of Analysis -- U.S. Cancer Morbidity and Mortality Trends -- U.S. Cancer Morbidity: Modeling Age-Patterns of Cancer Histotypes -- Risk Factors Intervention -- Cancer Prevention. | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. chttps://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a This book is the first of its kind to describe interdisciplinary approaches to biomedical studies. It views analyses of biomedical data sets, such as cancer morbidity and mortality, from a different and richer than classic epidemiological perspective by using mathematical modeling methods, including ones providing insights into probable mechanisms of human carcinogenesis. The book will be useful for many specialists, e.g., epidemiologists, oncologists, medical researchers, biologists, public health and environmental specialists, and specialists in mathematical modeling. Medical, biology and math undergraduates and postgraduates, as well as basic and applied researchers attempting to extend their studies in collaboration with other specialists in interdisciplinary teams, will find practical information here. Biomedical specialists could be interested in historical aspects of cancer treatment and prevention, mechanisms of carcinogenesis, cancer risk factors, cancer mortality and morbidity trends in the U.S. over a more than 50-year period, as well as specific features of cancer histotypes, and recent approaches to cancer prevention. Readers interested in analytic aspects can find information on existing and innovative approaches used in interdisciplinary studies such as stochastic process models, microsimulation of interventions, and empirical Bayes approaches. This book was written by authors with different backgrounds who teamed in an interdisciplinary group. Kenneth G. Manton, Ph.D. (Demography) is Research Professor of Demographic Studies at Duke University (Durham, NC). He was Head of the W.H.O. Collaborating Center for Research and Training in the Methods of Assessing Risk and Forecasting Health Status Trends. He has authored more than 450 peer-reviewed publications, including several books. Igor Akushevich, Ph.D. (Theoretical and Mathematical Physics), Center for Population Health and Aging at Duke University, authored more than 70 peer-reviewed publications. Julia Kravchenko, MD, Ph.D. (Internal Diseases, Biochemistry), Duke Comprehensive Cancer Center in the School of Medicine. She is author of more than 30 peer-reviewed publications. | ||
| 650 | |a Cancer |x Épidémiologie |z États-Unis | ||
| 650 | |a Cancer |x Mortalité |z États-Unis | ||
| 700 | 1 | |a Kravchenko, Julia. |4 aut | |
| 700 | 1 | |a Akushevich, Igor. |4 aut | |
| 776 | 0 | |t Cancer Mortality and Morbidity Patterns in the U.S. Population |b Texte imprimé |z 9780387569857 | |
| 776 | 0 | |t Cancer Mortality and Morbidity Patterns in the U.S. Population |b Texte imprimé |z 9781441926807 | |
| 776 | 0 | |0 132379023 |t Cancer mortality and morbidity patterns in the U.S. population |o an interdisciplinary approach |f K.G. Manton, Igor Akushevich, Julia Kravchenko |d 2009 |c New York |n Springer |p 1 vol. (XV-455 p.) |s Statistics for biology and health |z 978-0-387-78192-1 | |
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