Figure 4.

Performance of nanoNAM-based prediction of cancer risk and associated risk spaces. (A) Projection of CV-spectral, CV-1 and CV-infinity meta nuclear architectural properties onto a unit 2-sphere. The low- and high-risk patients lie on two separate hemispheres of the 2-sphere. (B) Receiver operator characteristics (ROC) of nu-SVM based risk classification on the independent validation sets generated using stratified bootstrapping, with six nanoNAM-based nuclear architectural properties being the input features. The 95% confidence interval of the ROC is also shown. (C) Negative and positive likelihood ratios of the risk-classifier depicting its ability to assess the respective odds of a patient being truly at low- or high-risk of developing cancer.