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Big data collections are aggregates of multiple datasets that are individually manageable, but as a group are too large to fit on disk.
Record linkage, originated in the statistics community, is used to identify those records in one or multiple datasets that refer to the same real-world entity [11].
The big data problem, according to them, consists of two distinct issues: Big data collections are aggregates of multiple datasets that are individually manageable, but as a group are too large to fit on disk.
Such datasets can be generated by combining multiple datasets that are expected to be subject to the same bias.
We found that RUNX1 expression was progressively reduced from low- to mid- to high-grade tumors in multiple datasets that include Ivshina breast dataset (n = 289, Figure 3B) and Lu breast dataset (n = 129, Supplementary Figure S3B).
Basically, MI creates multiple datasets that are copies of the original complete data.
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While this approach deals with a huge variability factor, the strength of the approach lies in using evidence in multiple PD datasets that may be very different in etiology, cause, and tissue source.
for such large-scale studies, and joint analysis of multiple heterogeneous datasets that include images as a component.
The Data Repository allows for the co-location of multiple electronic datasets that were created as part of clinical investigations.
The most useful index to clinicians, as well as to research investigators, will most likely consist of variables that consistently emerge as the strongest predictors in multiple epidemiological datasets that include a comprehensive range of measures.
The reverse order of preferences in Scenario 4 was a function of the multiple disparate datasets that were to be accessed and the fact that there was no separation of tasks, i.e. the researchers would be accessing identifiable data to create the linkage key and also doing the analysis.
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