Figure 3.

Schematic of model development for breast cancer risk prediction. Shown are block diagrams that describe the development stages for the final ensemble prognostic model. Building a prognostic model involves derivation of relevant features, training submodels and making predictions, and combining predictions from each submodel. The model derived the attractor metagenes using gene expression data, combined them with the clinical information through Cox regression, gradient boosting machine, and k-nearest neighbor techniques, and eventually blended each submodel’s prediction. From Cheng et al, Sci Transl Med. 2013;5:181ra50. Reprinted with permission from AAAS.