Automated exploitation of deep learning for cancer patient stratification across multiple types

Pingping Sun, Shijie Fan, Shaochuan Li, Yingwei Zhao, Chang Lu, Ka-Chun Wong, Xiangtao Li

Abstract: Recent frameworks based on deep learning have been developed to identify cancer subtypes from high-throughput gene expression profiles. Unfortunately, the performance of deep learning is highly dependent on its neural network architectures which are often hand-crafted with expertise in deep neural networks, meanwhile, the optimization and adjustment of the network are usually costly and time consuming.