○ or mapping to generic preference-based measures based on direct statistical association mapping.
To evaluate the responsiveness of generic and mapped preference-based measures based on the anchor of global change in health condition of colorectal cancer (CRC) patients.
Studies were included if; CRC-related HSUVs which were had not been reported previously which were ○ preference-based generic measure such as EQ-5D, HUI3, and SF-6D ○ or directly valued health state descriptions ○ or mapping to generic preference-based measures based on direct statistical association mapping.
CRC-related HSUVs which were had not been reported previously which were ○ preference-based generic measure such as EQ-5D, HUI3, and SF-6D ○ or directly valued health state descriptions ○ or mapping to generic preference-based measures based on direct statistical association mapping.
In particular, we introduce a quasi-entropy measure based on a geometric covering problem, three measures based on discrepancy from uniform distribution and one based on Euclidean minimum spanning trees.
Class-based measures are calculated according to the first component, Information-theoretic measures based on the second and hybrid measures based on both.
Those include measures based on molecular descriptors [10], measures based on molecular fragments (such as MACCS) and measures based on graph matching (such as maximum common substructure searches [11 13]).
Two uncertainty measures based on the base classifier predictions and the inconsistency of a predicted label set, respectively, were defined to select the most informative examples.
A number of cluster analysis methods has been described in [32] for identifying the number of clusters, which have been defined based on gap statistics, and other measures based on information criteria such as AIC (Akaike Information Criteria) or BIC (Bayes Information Criteria) which can be relevant in intra model or across models clustering.
Based on the detected conflicts interference mitigation measures based on coordinated reallocation of resources can be taken (step 3 in Figure 11).
Significant statistical differences were found between two subgroups concerning eight measures based on importance and three measures based on feasibility (Tables 5 and 6).
