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 ...

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 ...

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 ...

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 ...

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 ...

Data clustering is the process of placing data items into groups so that items within a group are similar and items in different groups are dissimilar. The most common technique for clustering numeric ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on technique for visualizing and clustering data. A self-organizing map (SOM) is a data structure that can be used ...