Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations.

Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations.

BACKGROUND:A unique archive of Big Data on Parkinson's Disease is collected, managed and disseminated by the Parkinson's Progression Markers Initiative (PPMI). The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the ea...

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Bibliographic Details
Main Authors: Ivo D Dinov, Ben Heavner, Ming Tang, Gustavo Glusman, Kyle Chard, Mike Darcy, Ravi Madduri, Judy Pa, Cathie Spino, Carl Kesselman, Ian Foster, Eric W Deutsch, Nathan D Price, John D Van Horn, Joseph Ames, Kristi Clark, Leroy Hood, Benjamin M Hampstead, William Dauer, Arthur W Toga
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4975403?pdf=render

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http://europepmc.org/articles/PMC4975403?pdf=render

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