How Does Dimensionality Reduction Aid in Cancer Diagnosis?
Dimensionality reduction techniques can help in the early diagnosis of cancer by identifying key biomarkers from high-dimensional datasets. For instance, PCA can be used to reduce the dimensionality of microarray data, enabling the identification of genes that are significantly differentially expressed between cancerous and non-cancerous tissues. This can lead to the discovery of potential diagnostic biomarkers.
