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The most important issue discussed here is the design of the data set required to train the artificial neural network.
The data set required for the training and testing of the proposed ANN model is obtained from Ref. [1].
Further, due to the cross-cultural nature of this research, a large portion of the data set required interpretation prior to transcription.
Similar data collection from other rural hospitals in geographically distinct areas may provide the data set required to re-evaluate the opportunities for regionalization of critical care in rural areas.
The advantage of this is that the baseline hazard distribution and parameter estimates are still unbiased, and the data set required for the analysis is considerably reduced when compared with the standard discrete-time model.
On studying the DYN case, the long but limited temporal span of the data set required the generation of artificially extended activity timelines, obtained by repeating the empirical timeline.
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In these analyses, "target" phylogenies are generated from large amounts of sequence data, and then subsamples of the full data set are analyzed to determine the fraction of the full data set required to recover the target phylogeny [ 8, 15, 16].
Keeping the E-value for constructing the BLAST similarity matrix constant, we observed the tendency that the larger data set required less stringent clustering parameters for the correct resolution of our gene families; that is, higher inflation values in case of TRIBE-MCL and lower E-value tree-cutoffs in case of MC-UPGMA (data not shown).
The statistical analysis of the study data set required a full extraction of the data.
Second, maximising the utility of the linked data set required a flexible data analysis that was logical and robust.
The data analysis for the whole data set required around 1,200 computing hours, and was performed in the GRID infrastructure provided by the Virtual Laboratory for e-Sciences project (www.vl-e.nl).nl
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CEO of Professional Science Editing for Scientists @ prosciediting.com