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
Link To Document :
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