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Herausgeber: 
  • Pere Puig
  • Elizabeth A. Ainsbury
  • Elisabeth Cardis
  • Jochen Einbeck
  • Guadalupe Gómez
  • M.Luz Calle
  • Extended Abstracts Fall 2015: Biomedical Big Data, Statistics for Low Dose Radiation Research 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Mai 2017  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Biomathematics / Biostatistics / C / Epidemiology & medical statistics / Life sciences# general issues / Mathematical and Computational Biology / Mathematics and Statistics / Maths for scientists / Statistics / Statistics for Life Sciences, Medicine, Health Sciences
    ISBN:  9783319556383 
    EAN-Code: 
    9783319556383 
    Verlag:  Springer Nature EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  Research Perspectives CRM Barcelona
    #07 - Trends in Mathematics  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  2292 gr 
    Seiten:  131 
    Illustration:  VII, 131 p. 24 illus., 17 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This two-part volume gathers extended conference abstracts corresponding to selected talks from the "Biostatnet workshop on Biomedical (Big) Data" and from the "DoReMi LD-RadStats: Workshop for statisticians interested in contributing to EU low dose radiation research", which were held at the Centre de Recerca Matemàtica (CRM) in Barcelona from November 26th to 27th, 2015, and at the Institut de Salut Global ISGlobal (former CREAL) from October 26th to 28th, 2015, respectively. Most of the contributions are brief articles, presenting preliminary new results not yet published in regular research journals.

    The first part is devoted to the challenges of analyzing so called "Biomedical Big Data", tremendous amounts of biomedical and health data that are generated every day due to the use of recent technological advances such as massive genomic sequencing, electronic health records or high-resolution medical imaging, among others. The analysis of this information poses significantchallenges for researchers in the fields of biostatistics, bioinformatics, and signal processing. Furthermore, other relevant challenges in biostatistical research, not necessarily involving big data, are also discussed.

    In turn, the second part is dedicated to low dose radiation research, where there is a need to fully understand and characterize potential sources of uncertainty before they can be reduced. Further, the book demonstrates why formal uncertainty analysis has the potential to provide a common platform for multidisciplinary research in this field.

    This book is intended for established researchers, as well as for PhD and postdoctoral students who want to learn more about the latest advances in these highly active areas of research.

      
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