Before revision:  The results showed that transfer learning approach outperformed the traditional radiomics model on PDAC data. A transfer learning approach may fill the gap between radiomics and deep learning analytics for cancer prognosis and improve performance beyond what CNNs can achieve using small datasets  .
After revision:  The results showed that transfer learning approach outperformed the traditional radiomics model (0.56) as well as a CNN model trained from scratch (0.50). These results suggest that deep transfer learning may significantly improve prognosis performance using small datasets .