Population Biobank Studies: A Practical Guide
This book describes some of the key epidemiological principles, scientific approaches and quality assurance frameworks required to design and conduct biobank studies in various settings. Using examples from contemporary biobanks, the book addresses the design features and practical procedures needed in order to launch and manage biobank studies, including consent and regulatory approval, the organisation of field work, management of data and biological samples, follow-up and verification of disease outcomes, development of IT systems for data collection, quality assurance and study management.Over the last two decades, several large biobank s…
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Produktdetails
- ISBN: 978-981-1576-68-3
- EAN: 9789811576683
- Produktnummer: 38109386
- Verlag: Springer Singapore
- Sprache: Englisch
- Erscheinungsjahr: 2021
- Seitenangabe: 220 S.
- Masse: H23.5 cm x B15.5 cm x D1.2 cm 341 g
- Auflage: 1st ed. 2020
- Abbildungen: Paperback
- Gewicht: 341
Über den Autor
Zhengming Chen is a Professor of Epidemiology at the Nuffield Department of Population Health, University of Oxford, UK. He qualified in Medicine at Shanghai Medical University in China in 1983 and obtained a DPhil in Epidemiology from the University of Oxford in 1992. His main research focus has been on the determinants of chronic disease and advancement of evidence-based medicine. Since the mid-1990s, he has initiated and conducted several large prospective cohort studies and randomised trials of treatment for heart attack, stroke and cancer, yielding important findings that have since changed clinical practices and health policies worldwide. Most notably, he initiated, designed and co-directs, as the UK study PI, the China Kadoorie Biobank (CKB) study of over 500,000 adults, which has applied innovative approaches and methodologies for participant recruitment, data collection, quality assurance, study management and follow-up. He currently leads a large research team in Oxford, with expertise in epidemiology, population health, genomic medicine, and data science.
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