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. 2022 Apr 19;304(2):406–416. doi: 10.1148/radiol.212137

Figure 1:

Flowchart shows workflow for training and testing of a two-stage classifier. Each stage consists of a binary classifier optimized for its own respective reduced-feature set obtained by sparse regression analyses. The first stage passes the subgroup composed of wingless (WNT) and sonic hedgehog (SHH) to the second stage for further separation. CE = contrast enhanced, LASSO = least absolute shrinkage and selection operator, NN = neural network.

Flowchart shows workflow for training and testing of a two-stage classifier. Each stage consists of a binary classifier optimized for its own respective reduced-feature set obtained by sparse regression analyses. The first stage passes the subgroup composed of wingless (WNT) and sonic hedgehog (SHH) to the second stage for further separation. CE = contrast enhanced, LASSO = least absolute shrinkage and selection operator, NN = neural network.