Before revision:  In this second approach, we also seek the answer to the fundamental question about the goodness of "deep features" for unsupervised tumor classification . Finally, we study the effect of unsupervised representation learning using Generative Adversarial Networks (GAN) on classification performance .
After revision:  In this second approach, we also seek the answer to the fundamental question about the goodness of "deep features" for unsupervised tumor classification .