Data clustering remains an essential component of unsupervised learning, enabling the exploration and interpretation of complex datasets. The field has witnessed considerable advancements that address ...

Ensemble clustering methods combine multiple clustering results to yield a consensus partition that is often more robust, accurate and stable than any single clustering solution. These techniques ...

Identification of differentially expressed genes and clustering of genes are two important and complementary objectives addressed with gene expression data. For the differential expression question, ...

Multivariate analysis in statistics is a set of useful methods for analyzing data when there are more than one variables under consideration. Multivariate analysis techniques may be used for several ...

Monitoring brain injury biomarkers and glucose variation in patients who have suffered an acute cranial injury during the entire first week of hospitalisation can provide a more accurate picture of ...