• DocumentCode
    2690713
  • Title

    (1) Obstacles and options for big-data applications in biomedicine: The role of standards and normalizations

  • Author

    Chute, Christopher G.

  • fYear
    2012
  • fDate
    4-7 Oct. 2012
  • Firstpage
    1
  • Lastpage
    1
  • Abstract
    Advances in computing capabilities are palpably evident throughout many industries manifest by unprecedented, large-scale data integration and inferencing. Branded as "big-data" in many cases, the question of whether such techniques can leverage advances in biomedicine and clinical practice are obvious. High-throughput clinical analytics, synthesizing genomic and clinical attributes of a particular patient, portends predictive models that can directly influence clinical care decisions. However, to make this widely shared vision practical and scalable, barriers attributable to data heterogeneity dominate. Methods and strategies to increase the comparability and consistency of healthcare related data will be discussed.
  • Keywords
    bioinformatics; biomedical engineering; data handling; health care; big data applications; biomedicine; healthcare related data; high throughput clinical analytics; large scale data inferencing; large scale data integration; predictive models; Bioinformatics; Educational institutions; Genomics; Informatics; Medical services; Standards; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine (BIBM), 2012 IEEE International Conference on
  • Conference_Location
    Philadelphia, PA
  • Print_ISBN
    978-1-4673-2559-2
  • Electronic_ISBN
    978-1-4673-2558-5
  • Type

    conf

  • DOI
    10.1109/BIBM.2012.6392651
  • Filename
    6392651