Sentence examples for interpretation of cluster from inspiring English sources

Emphasis is placed on both qualitative and quantitative aspects corresponding, respectively, to the clinical interpretation of cluster definitions, and the robustness or sensitivity of the classification procedures to changes in patient profiles over time.

This problem, which we discuss below, deserves wider recognition by trialists and clinicians participating in the design, conduct, and interpretation of cluster randomised trials.

The relationship between the pattern of clustering observed on the phylogenetic tree and the characterization of a clearly defined sub-population supports the interpretation of cluster identification as means to identify a group at risk of HIV infection.

These pathways are then also clustered to distill typical pathways, enabling interpretation of clusters by experts.

It also permits to inspect which features are similar among sub-groups, providing a basis for a more informed bio-physical interpretation of clusters and sub-clusters.

These challenges include rapid appraisals of how to distinguish from among multiple coevally formed dams that are most hazardous; suitable engineering solutions for stabilizing landslide dams; management of massive sediment pulses and their risks—in the wake of landslide-dam failures; and the paleoseismological interpretation of clusters of coeval landslide dams.

Heagerty has developed fundamental methods for longitudinal studies with a focus on prognostic model evaluation and structural longitudinal models, and he has detailed methods for the design, analysis, and interpretation of cluster-randomized trials conducted within health care delivery systems.

In future work, we plan to compare multi-layer clustering with redescription mining and to test if results of redescription mining might be used for human understandable interpretation of clusters obtained by the multi-layer approach.

The use and interpretation of clustering agreement measures can be improved by the estimation of suitable confidence intervals (CI).

Age stratified syndromic surveillance with a multivariate space-time scan statistic [29] may further facilitate quick interpretation of clusters by revealing the affected age groups.

Increasing the number of clusters is statistically preferable to increasing the number of households or individuals within each cluster as it provides greater interpretation of cluster-to-cluster variation, which is likely to be large in active conflict settings.