High dimensionality refers to datasets with a large number of variables or features. In the context of cancer research, this often means analyzing complex biological data such as genomic sequences, proteomic profiles, and imaging data from multiple sources. These datasets can contain thousands or even millions of features, making traditional analytical methods inadequate.
