Fig. 2.

Illustration showing(a) the radiogenomic neural network's architecture, (b) transfer learning using a deep transcriptomic autoencoder, and interpretation methods using (c) gene masking and (d) gene saliency. Pretrained weights learned in the autoencoder were transferred to a radiogenomic model, where weights were frozen (non-trainable, long red arrows) and/or fine-tuned (trainable, dashed red arrow) during radiogenomic training. (Color version of this figure is available at Bioinformatics online.)