Sentence examples for predictive centrality from inspiring English sources

The fact that the more dynamic aspects of our study - both the trajectories of the MRSA-positive patients and the fact that flow is the most predictive centrality measure for the outbreak sizes - showed clearer deviations from the expected results, suggests that dynamic representations of the patient flow at a unit level could be a fruitful direction for future studies.

R 2 can also be interpreted as a measure of the strength of the descriptive or predictive power of the centrality measure.

This is because the predictive power of infection betweenness centrality for NB is similar across the networks as shown in Figure 3a.

In the OHSU sample, betweenness centrality measures contained predictive information for the classification of ADHD and control subjects with a score of 73%.

In this study, we investigated the use of network centrality measures as predictive features to discriminate between typical developing children and ADHD patients with both inattentive and combined presentations.

The strategy behind our analysis was to establish which subset of centrality measures had greater predictive ability for sentencing outcomes in the Caviar Network case.

This study has shown that social network centrality indicators have good predictive abilities that can strengthen the efforts of criminologists to explain criminal trial sentencing outcomes using data on the communication behavior of a criminal network.

Network centrality measures contained little predictive information for the discrimination between ADHD patients and healthy subjects.

Analyses of protein-protein interaction networks (PPINs) have revealed that genes with high betweenness centrality may be common predictive markers of chemosensitivity [ 25].

When the whole sample was used, none of the centrality measures had a relevant predictive power beyond chance.

Thus, they explore whether a predictive model of sentencing outcome can be constructed from measures of degree centrality, betweenness centrality, and closeness centrality together with graph density and centralization metrics.