Exact(1)
17 Because categorised AKI is easy to interpret, if it meets criteria for significance, we will primarily focus on this outcome.
Similar(59)
However, the parameters of a model are easier to interpret if the same reference point is used for all inflation adjustments.
The results are easier to interpret if we consider the top-scoring TFs and the top-scoring motifs as two separate lists.
Also, I think the data from these experiments would be much easier to interpret if displayed as histograms (e.g. something like Figure 2 in the recent eLife paper from Amon and Torres) in addition to the scatter plot view.
Patient management studies are easiest to interpret if it can be assumed that clinicians use all test information appropriately in a standard way, so that a change in patient management can be attributed to the test itself rather than to variations in the clinicians' behaviour.
All continuous variables are reported as medians and interquartile ranges (IQRs) because some of the data was not normally distributed (e.g. length of stay) and it is easier to interpret if all continuous variable are reported with the same summary statistics.
His stream-of-consciousness lyrics are never easy to interpret, but if you imagine him in his pre-Yes day job as a milkman, they almost make sense.
While condition IIb may be an artefact caused by mislabelled GenBank accessions, it is also known that some Pseudoperonospora species are not particularly host-specific [47], and all in all the clusters would be less easy to interpret biologically if IIb were a frequent condition.
Query averages are easy to interpret, and if usage favors certain types of queries, the average can be weighted, e.g. linearly or quadratically with the number of proteins in a family (Green and Brenner, 2002).
One of the first conclusions that we drew was that we should continue using rule learning algorithms for creating the decision trees, since the knowledge representation is very easy to interpret, analyse and modify, if you want to include your own knowledge.
It is computationally less intensive and easy to interpret, but can be unstable if the model is inadequately trained with limited data.
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