Transitivity Clustering is a method for the partitioning of biological data into groups of similar objects, such as genes, for instance. It provides integrated access to various functions addressing ...

This work has evaluated the potential superiority of a morphomolecular classification based on the combination of clinicopathologic and molecular features of colorectal cancers. A cohort of 126 ...

Cluster analysis can aid in identifying subgroups of patients with similar patterns of comorbid conditions for targeted care management. We identified a cohort of adult members of an integrated health ...

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

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...

Spectral clustering is quite complex, but it can reveal patterns in data that aren't revealed by other clustering techniques. Data clustering is the process of grouping data items so that similar ...

Clustering is a data science technique in machine learning that groups similar rows in a data set. After running a clustering technique, a new column appears in the data set to indicate the group each ...

Conventional clustering techniques often focus on basic features like crystal structure and elemental composition, neglecting target properties such as band gaps and dielectric constants. A new study ...

Ready or not, the artificial intelligence revolution is here and marketers who have embraced it have a serious competitive edge. One of the most exciting applications is the ability to gain insights ...