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